Forthcoming articles

International Journal of Modelling, Identification and Control

International Journal of Modelling, Identification and Control (IJMIC)

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International Journal of Modelling, Identification and Control (96 papers in press)

Regular Issues

  • A survey of control strategies for grid connected wind energy conversion system based permanent magnet synchronous generator and fed by multi-level converters   Order a copy of this article
    by Youssef Errami, Abdellatif Obbadi, Smail Sahnoun 
    Abstract: In this study, two control strategies for speed and power control of three-level neutral-point (3L-NPC) clamped back-to-back converters in Wind Energy Conversion System (WECS) with Permanent Magnet Synchronous Generator (PMSG) are proposed. The system consists of Generator Side Converters (GSCs) and Grid Side Converter (GSC) which share a common DC-link capacitor. The proposed control laws combine Sliding Mode Control (SMC) and Vector Oriented Control (VOC) to maximise the generated power from Wind Turbine Generators (WTGs). Considering the variation of wind speed, the GSC injects the generated power into the AC network, regulates DC-link voltage. Also, it is employed to achieve unity power factor. The GSCs are employed to achieve Maximum Power Point Tracking (MPPT). To validate the proposed approaches, simulations are carried out with MATLAB/Simulink software. The simulation results demonstrate a good performance in various scenarios.
    Keywords: wind electrical system; PMSG;3L-NPC; MPPT; SMC; VOC; grid.

  • Nonlinear controller for MPPT based photovoltaic system under variable atmospheric conditions   Order a copy of this article
    by Fatima Ez-Zahra Lamzouri, El-Mahjoub Boufounas, Aumeur El Amrani 
    Abstract: This paper depicts a robust controller design combining backstepping approach and sliding mode controller (BSMC) based maximum power point tracking (MPPT) for a photovoltaic (PV) system. The investigated PV system is based on a PV module as power source, a DCDC boost converter and a resistive load. A modified conventional perturb and observe (P&O) algorithm based MPPT control is designed, which presents good performances under constant atmospheric conditions. However, the solar radiation and cell temperature variations present a major effect on the PV output power. Thus, the proposed BSMC controller can allow to the PV system operate around the estimated MPPT under variable atmospheric conditions. Furthermore, the Lyapunov theory is used in order to demonstrate the stability of the PV system with BSMC controller. Moreover, the investigated control approach effectiveness is exhibited by comparing the developed BSMC controller, conventional sliding mode controller (SMC) and modified P&O algorithm. For the proposed BSMC approach, the obtained results with simulation illustrate good efficiency in terms of transition response, tracking error and fast response to atmospheric conditions variation.
    Keywords: photovoltaic system; maximum power point tracking; sliding mode control; backstepping approach; perturb and observe algorithm.

  • Modelling, identification, implementation and MATLAB simulations of multi-input multi-output proportional integral-plus control strategies for a centrifugal chiller system   Order a copy of this article
    by Nicolae Tudoroiu, Mohammed Zaheeruddin, Roxana-Elena Tudoroiu 
    Abstract: The objective of this paper is to investigate a new design and real-time implementation approach of a predictive proportional integral-plus (PIP) closed-loop control strategy for a centrifugal chiller HVAC system. As a case study, a dynamic model of a centrifugal chiller system developed in a previous study was considered. By using this analytical model as the plant, linear discrete-time polynomial multi-input multi-output (MIMO) autoregressive moving average models with exogenous input (ARMAX) were developed. The choice of ARMAX models is warranted since such models are simple in their structure and capture the dynamics of the centrifugal chiller plant which is of high complexity in terms of dimension and encountered nonlinearities. Fundamentally, these identified models use the least-squares estimation (LSE) method to evaluate the polynomials coefficients and model parameters implemented using specific tools provided by MATLABs system identification toolbox. The new modelling approach is beneficial for simulation purposes to prove the efficiency of the proposed closed-loop control strategy, the tracking performance, and its robustness to possible changes in the load disturbance and noise level of measurement sensors.
    Keywords: centrifugal chiller; MIMO ARMAX model; PI-Plus control; least-squares estimation; HVAC control systems.

  • Kinematic modelling and simulation of PID controlled SCARA robot with multiple tool end effectors   Order a copy of this article
    by M. Saravana Mohan, V. Anbumalar, S. Thirumalai Kumaran 
    Abstract: The mechatronics approach is adopted to develop and control electromechanical systems such as robots. In this paper, the three-dimensional (3D) Computer Aided Drawing (CAD) model of a Selective Compliant Assembly Robot Arm (SCARA) robot with a multiple tool end effector (MTEE) is developed using SolidWorks software. A novel attempt of PID controller based simulation is carried out in SimMechanics simulation environment by MATLAB software. By linking CAD modelling, SolidWorks and MATLAB/SimMechanics software, the 3D CAD model of the SCARA is transformed into a series of blocks representing the multibody electromechanical system. The motion-sensing capability and the simulation modes of SimMechanics incorporated with PID controller are applied for positioning the end effector of the manipulator accurately. The results of the SimMechanics simulation presented in this paper infer that the position of the manipulator can be controlled precisely.
    Keywords: SCARA; multiple tool end effector; SolidWorks; SimMechanics; multibody simulation; PID controller.

  • Robust finite-time sliding mode control of twin rotor MIMO system   Order a copy of this article
    by Kaushik Raj, Santosh Kumar Choudhary, Venkatesan Muthukumar 
    Abstract: In this article, a robust finite-time sliding mode control of the Twin Rotor MIMO System (TRMS) is discussed. This helicopter laboratory model is highly nonlinear in characteristics and coupling dynamics between main and tail rotors. The main purpose of this paper is to investigate finite-time sliding mode control for pitch and yaw angles of TRMS, either for posture stabilisation or trajectory tracking. Moreover, these angles are used commonly to determine the hovering posture of a helicopter. The article first briefs the dynamical model of TRMS and then it adopts a finite-time sliding mode control technique to achieve the desired trajectory or posture stabilisation. Numerical simulation results are demonstrated and verify the effectiveness of the control technique.
    Keywords: twin rotor MIMO system; robust control; finite-time sliding mode control; nonlinear control systems; uncertain system; helicopter system.

  • The condition number of the static gains matrix as a quality index in LPV IO MIMO multi-objective identification   Order a copy of this article
    by Oscar Daniel Chuk, Carlos Gustavo Rodríguez Medina, Enrique Antonio Núñez, Gustavo Scaglia 
    Abstract: A quality index of linear multivariable models is presented in this article, with application to linear systems with variable parameters LPV systems. The index is based on the condition number of the static gains matrix of the process. An example of use in the identification by means of multiobjective optimisation of a non-linear process of two inputs and two outputs verifies the importance of the use of this index, in particular, if the identified model will be used for the synthesis of controllers.
    Keywords: condition number; modelling; multivariable systems; linear parameter varying systems; multi-objective optimisation.

  • Self-Learning Salp Swarm Optimization Based Controller Design for Photovoltaic Reverse Osmosis Plant   Order a copy of this article
    by Naresh Patnana, S. Pattanaik, V.P. Singh, R. Kumar 
    Abstract: In this work, a self-learning salp swarm optimisation (SLSSO) based controller design is proposed for a photovoltaic reverse osmosis (RO) desalination unit. The SLSSO algorithm is proposed in order to improve the performance of salp swarm optimisation. The photovoltaic RO model considered is basically an interacting two-input-two-output (TITO) system. The interacting TITO system is first converted into two non-interacting sub-systems by designing an appropriate decoupler. Then, two proportional-integral-derivative (PID) controllers are designed by minimising the integral-of-squared-error (ISE) of the respective non-interacting sub-systems. The ISE is designed in terms of alpha and beta parameters for ease of simulation. This designed ISE is minimised using the proposed SLSSO algorithm. For showing the efficacy of SLSSO-assisted PID controllers, other PID controllers are also obtained using some state-of-art optimisation algorithms. The results prove that SLSSO-assisted PID controllers outperform other PID controllers.
    Keywords: decoupler; desalination; photovoltaic RO system; salp swarm optimisation; tuning; water treatment.

  • Minimal overshoot V-F control for islanded microgrids   Order a copy of this article
    by Ehab Bayoumi, Hisham Soliman, Mostafa Soliman 
    Abstract: Islanded microgrids dynamics are greatly affected by the controllers gains and power-sharing parameters. This paper considers an islanded microgrid containing two distributed generation (DG) units. Each DG has its PWM inverter for three phases. Each inverter has two control loops in cascade. The inner loop is a current loop and the outer loop is a voltage loop. The controller of each loop is designed to provide good dynamic performance in terms of minimal percentage overshoot and overall system stability. Particle Swarm Optimisation (PSO) is used to design the current and voltage controllers to achieve the desired performance. The proposed controllers are compared with the conventional technique (Ziegler and Nichols) to show the excellence of the proposed technique. Different test scenarios, such as voltage and current tracking and load parameters variation, are used to examine the proposed design. Test results validate and endorse the effectiveness and superiority of the proposed controllers compared with the traditional one, in addition to enhancing the stability of the given microgrid system.
    Keywords: V-F control; microgrids; distributed generation; particle swarm optimisation.

  • Application of ellipsoidal approximation into target tracking for multi UAVs formation cooperative detection   Order a copy of this article
    by Wang Jianhong, Meng He, Ricardo A. Ramirez-Mendoza 
    Abstract: In this paper, the ground target positioning and tracking algorithm for cooperative detection of multi UAVs formation is studied. Then a real time and rapid algorithm is discussed based on UAV airborne electro-optical sensors. Because some information is embodied in the considered state, two state estimation problems for linear or nonlinear stochastic systems are considered under the conditions of statistical noise and unknown but bounded noise, respectively. First, in case of known probabilistic distribution of noise, the unscented Kalman filter algorithm is applied to estimate the unknown state for target tracking process. Secondly, to relax the strict condition on white noise in Kalman filtering theory, the problem of target tracking or state estimation is reduced to derive the inner and outer ellipsoidal approximations for the state in the case of unknown but bounded noise. The special case and more general case are all studied with the number of the ellipsoids, and some alternative forms are derived to obtain the approximate outer and inner ellipsoidal approximations. Finally, one simulation example confirms our theoretical results proposed in this paper.
    Keywords: multi UAVs formation; cooperative detection; target tracking; ellipsoidal approximation.

  • Comparative studies between the Bayesian estimation and the maximum likelihood estimation of the parameter of the uniform distribution   Order a copy of this article
    by Bao Xu 
    Abstract: The point estimation of the parameter ? of the uniform distribution U(0,?) is discussed. The general form of the Bayesian estimation of ? is investigated under the weighted square loss function in the framework of Bayesian statistics, and the precise form of the Bayesian estimation of ? is obtained, based on the given Pareto conjugate prior distribution. The comparisons between the Bayesian estimation obtained in the framework of Bayesian statistics and the maximum likelihood estimation obtained in the framework of classical statistics are studied from theory and simulation, respectively. Results show that the Bayesian estimation of ? under the weighted square loss function is smaller than the maximum likelihood estimation of ? in the framework of classical statistic in numerical value, and the Bayesian estimation that obtained is the maximum likelihood estimations of the corresponding functions of ?, respectively.
    Keywords: uniform distribution; Bayesian estimation; loss function; conjugate prior distribution; maximum likelihood estimation.

  • A tracking method for inland river ships based on dual filters   Order a copy of this article
    by Lei Xiao, Minghai Xu, ZhongYi Hu 
    Abstract: Recently, tracking algorithms based on correlation filter have achieved high performance in the video target tracking field. They have achieved good results in automobile and human tracking with long-term non-constrained video stream. However, when there is occlusion between ships, the tracking strategy of inland river CCTV (closed-circuit television) system is prone to drift. When the current video frame searches the moving ships exhaustively, it is found that the target ship and the background change greatly. This paper deeply analyses the problems existing in the correlation filter tracking system and the characteristics of the target scene, to deal with the problem of inland river ship tracking under severe occlusion. In this paper, we first apply variance filter to correlation filter tracking algorithm to significantly reduce candidate samples. Secondly, we propose an occlusion aware model to solve the problem of severe occlusion during target motion. Experimental results show that the proposed algorithm is more robust to occlusion than other algorithms.
    Keywords: correlation filter; variance filter; occlusion; ship tracking.

  • Modelling and dynamic surface backstepping recursive sliding mode control for the speed and tension system of the reversible cold strip rolling mill   Order a copy of this article
    by Le Liu, Jia-Ping Qiang, Yi-Ming Fang 
    Abstract: For the speed and tension system of the reversible cold strip rolling mill, a dynamic surface backstepping recursive sliding mode control (DSBRSMC) strategy is proposed based on the immersion and invariance (I&I) adaptive method and the nonlinear disturbance observer (NDO). First, by using the mechanism modelling method, a relatively complete mathematical model for the speed and tension system of the reversible cold strip rolling mill driven by alternating current (AC) asynchronous motors is established. Next, the I&I adaptive method is adopted to estimate the perturbation parameters of the system, and the NDO is developed to observe the system uncertainty. Again, controllers for the speed and tension system of the reversible cold strip rolling mill are presented by combining the backstepping control, the dynamic surface control, and the recursive sliding mode control. Theoretical analysis shows that the controller guarantees closed-loop systems stability in the Lyapunov sense. Finally, simulation research is carried out on the speed and tension system of a reversible cold strip rolling mill by using the actual data, and results show the validity of the proposed control strategy.
    Keywords: reversible cold strip rolling mill; alternating current asynchronous motor drive; immersion and invariance; nonlinear disturbance observer; dynamic surface backstepping control; recursive sliding mode control.

  • Gap identification strategy for mobile robot navigation in static and dynamic environments   Order a copy of this article
    by Rekik Chokri 
    Abstract: This paper presents a new strategy of mobile robot navigation inspired from Follow The Gap and Grouping Obstacles methods in static and dynamic environments. In this work, we have proposed a solution based on gap identification for the problem of obstacle avoidance. The mobile robot scans the surrounding through a laser sensor, then chooses the safest gap between the obstacles to reach the target. After that, the direction of the mobile robot is given by a fuzzy logic controller. This algorithm have shown its adaptability in cluttered environment and have produced satisfied results comparing to the methods suggested in previous works. On the other hand, we have added a new fuzzy logic controller in the case of dynamic obstacles to command the linear velocity of the robot. This approach was tested in some simulations, and have shown its efficiency in generating shorter and optimal pathes in a small time, with represents a great advantage.
    Keywords: mobile robot; willing gap; fuzzy controller; obstacle avoidance.

  • Modified model-compensation ADRC controller and its application in PMSM current loop   Order a copy of this article
    by Yingning Gao, Xin Huo, Kemao Ma, Hui Zhao 
    Abstract: Active disturbance rejection control (ADRC) is now widely applied in motor drives owing to its advantages like independence of system models and better disturbance rejection ability. For the current loop of PMSM, the uncertainties like model coupling and parameter variation can be estimated and compensated by ADRC. Considering that the total disturbance of current loop can be partially compensated by available plant characteristics, the idea of model compensation can be applied to the ADRC controller. However, the filter link in the current feedback loop is usually ignored in the conventional model compensation approach. Therefore, a modified model-compensation ADRC current control strategy is proposed with the filter link effect considered in this paper. Simulation and experimental results show that better current tracking performance is achieved by the proposed control strategy.
    Keywords: model-compensation ADRC; total disturbance; filter link; current loop.

  • Under-actuated decoupling controller design and analysis based on U model   Order a copy of this article
    by Rui Wang, Yu Wang, Hui Sun 
    Abstract: This paper proposes a controller design algorithm for the combination of under-actuated system control and U model control. First, the decoupling coordinate transformation of the under-actuated system greatly helps to reduce the complexity of the system. Second, inspired by the principles of U model, the control law of the under-actuated nonlinear system is established by using the linear pole placement method and satisfies the desired performance indexes. Furthermore, the method is able to be widely applied to different under-actuated nonlinear systems as well. Finally, MATLAB simulation verification confirms the feasibility of the algorithm.
    Keywords: under-actuated systems; U model; decoupling.

  • Induction motor current ripple minimisation with PV-based SEPIC-cascaded inverter   Order a copy of this article
    by Walid Emar, Zayed Huneiti, Zakariya Al-Omari 
    Abstract: In this study, an induction motor is supplied from a SEPIC converter that is extracting a direct current from a photovoltaic solar cell system. The DC output voltage of SEPIC is converted into a five-level AC output voltage using a cascaded H-bridge inverter. The five-level cascaded inverter with the SEPIC converter serves as a good interface utility between PV supply sources and the induction motor. This enables supplying the motor by a multi-level high-frequency output voltage and current. Various PWM modification techniques for the multi-level inverter are discussed in this study based on the multicarrier redistribution technique. The current and voltage total harmonic distortion (THD) level of the inverter is used to investigate the harmonic contents generated in the output waveform of the induction motor. Note that the total harmonic distortion (THD) generated at the output of the inverter and the input of the motor varies depending on the inverter topology, the levels of the multi-level inverter, and the modulation index. This is an important coefficient that affects the power losses and efficiency of the motor. To minimise the harmonic content of the induction motor and inverter, a new topology of multi-carrier PWM techniques, known as the Hybrid Trapezoidal Technique (HTrap), is used to control the switching of the five-level cascaded inverter (MLCI). This technique proved to have a reduced electromagnetic interference (EMI), as well as the lowest total harmonic distortion (THD), harmonic factor (HF), and crest factor (KF) without using inductors compared with other multicarrier PWM techniques. This method with the HTrap technique ensures maximum efficiency of the whole set (PV-based SEPIC-inverter-motor) and maximum power transfer under all operating conditions. This study also deals with the SEPIC converter performance within the region of discontinuity. The discontinuous modes, along with the voltage and current waveforms, are presented. Different technical parameters are also investigated and recorded. The main attention is focused on the analysis, experimental testing and simulation of the fundamental SEPIC converter, along with the five-level inverter and a three-phase induction motor. Simulations were performed using Simplorer 7 or Matlab and Excel to validate the concepts of SEPIC converter and multi-level cascaded inverter for grid-connected PV systems to supply AC motors.
    Keywords: induction motor control; SEPIC converter; harmonic content; five-level cascaded H-bridge three-phase inverter; hybrid trapezoidal carrier PWM technique; generic block diagram.

  • A new family of 5-D, 6-D, 7-D and 8-D hyperchaotic systems from the 4-D hyperchaotic Vaidyanathan system, the dynamic analysis of the 8-D hyperchaotic system with six positive Lyapunov exponents and an application to secure communication design   Order a copy of this article
    by Khaled Benkouider, Toufik Bouden, Mustak E. Yalcin, Sundarapandian Vaidyanathan 
    Abstract: This work reports a new family of 5-D, 6-D, 7-D and 8-D hyperchaotic systems derived successively from the 4-D hyperchaotic Vaidyanathan system (2018). The new 8-D hyperchaotic system possesses six positive Lyapunov exponents. We discuss the dynamic properties of the new 8-D hyperchaos system, describe its self-synchronisation and provide an application in secure communication. An equivalent electronic circuit of the 8-D hyperchaos is implemented using Multisim software to validate the physical feasibility of the system. As an application to secure communications, a new hyperchaotic transmission scheme is developed based on the drive-response synchronisation method and using all the 8-D hyperchaos signals generated by the proposed system. With its six positive Lyapunov exponents, the proposed 8-D hyperchaos system generates high complex behaviour. Thus, the new 8-D hyperchaos system can be deployed in many engineering applications, such as cryptosystems and secure communication.
    Keywords: chaos; hyperchaos; hyperchaotic systems; circuit design; synchronisation; secure communication.

  • A new multistable hyperjerk dynamical system with self-excited chaotic attractor, its complete synchronisation via backstepping control, circuit simulation and FPGA implementation   Order a copy of this article
    by Sundarapandian Vaidyanathan, Esteban Tlelo-Cuautle, Aceng Sambas, Leutcho Gervais Dolvis, Omar Guillén-Fernández, Babatunde A. Idowu 
    Abstract: In this work, we report a new 4-D chaotic hyperjerk system and present a detailed dynamic analysis of the new system with Lyapunov exponents, bifurcation plots, etc. We find that the new hyperjerk system exhibits multistability and coexisting chaotic attractors. The hyperjerk system has a unique saddle-focus rest point at the origin, which is unstable. This shows that the new chaos hyperjerk system has a self-excited chaotic attractor. As an application of backstepping control, we obtain new results for the global chaos complete synchronisation of a pair of chaotic hyperjerk systems. A circuit model using MultiSim of the new chaotic hyperjerk system is designed for applications in practice. Finally, an FPGA-based implementation of the new chaotic hyperjerk dynamical system is performed by applying two numerical methods, and their corresponding hardware resources are given.
    Keywords: chaos; chaotic systems; hyperjerk; backstepping control; synchronisation; circuit design; FPGA design.

  • A hybrid CSS-GW algorithm for finding optimum location of multi semi-active MR dampers in building   Order a copy of this article
    by Farzad Raeesi, Hedayat Veladi, Bahman Farahmand Azar, Siamak Talatahari 
    Abstract: Selecting a place where dampers should be installed has significant importance to achieve the best performance of them in reducing dynamic responses. Different methods can be used to find the optimum location of dampers in structures. One of the most widely used methods is the meta-heuristic algorithms. In this paper, charged system search (CSS) and grey wolf (GW) algorithms are hybridised as HCSS-GW, to improve the searching abilities in finding the optimum location of the multi-magnetorheological (MR) fluid dampers in structural buildings. In this proposed hybrid algorithm, the charged system search algorithm helps the grey wolf in generating the initial positions. In other words, the solutions of the CSS algorithm are regarded as the initial population of the GW, instead of generating initial random positions. To illuminate the validity of the HCSS-GW algorithm in solving other optimisation problems, some benchmark test functions are selected to compare the hybrid algorithm with both standard CSS and GW algorithms in evolving best solutions. The obtained results indicate that the HCSS-GW is highly robust and accurate in comparison with its constituent algorithms and can be used successfully in finding optimum locations of dampers in different buildings.
    Keywords: semi-active MR damper; optimisation; hybrid algorithm; optimum location.

  • Incremental backstepping robust fault-tolerant control with improved IHSTD for RLVs   Order a copy of this article
    by Wu Liu, Yanli Du, Erwin Mooij, Haibing Lin 
    Abstract: Aiming at unknown disturbances/uncertainties, partial effectiveness loss fault (PELF) and stuck failure (SF) of the actuator, a composite robust fault-tolerant control strategy based on incremental backstepping (IBS) is proposed for a reusable launch vehicle (RLV) during re-entry. By converting PELF into disturbances/uncertainties, this paper presents an incremental form of disturbance observer based on an improved inverse hyperbolic sine tracking differentiator (IHSTD) to compensate these interference terms originally ignored in the IBS design process. Furthermore, a failure symbol matrix is set to control the on-off states of the reaction control system of the RLV to make up for the missing torque of the actuator SF, which can strengthen the fault-tolerance capability of the control system. The simulation results show that the tracking effect of the proposed method on the attitude-angle commands is better than traditional backstepping with disturbance observer, and the presented control allocation strategy is capable of timely resolving the actuator SF problem to ensure stability of flight.
    Keywords: reusable launch vehicle; fault-tolerant control; incremental backstepping; tracking differentiator disturbance observer; reaction control system.

  • Multipartite tracking consensus of linear MASs with arbitrarily projective parameters   Order a copy of this article
    by Liuxiao Guo, Jing Chen, Manfeng Hu, Zhengxian Jiang 
    Abstract: This paper proposes distributed bipartite and multipartite tracking consensus for linear multiagent systems (MASs) with arbitrarily non-zero projective parameters in networks, which includes traditional consensus, bipartite consensus and group consensus as its special items. Based on the projective similarity transformation and Riccati inequality, novel types of protocol are designed to achieve bipartite and multipartite consensus exponentially without analysing the signed graph, as in most current literature on bipartite problems. For obtaining multipartite consensus involving less global information, the distributed protocols with adaptive tuning of the coupling strength are further adopted. Finally, the theoretical results are illustrated through two numerical simulation examples when linear systems are equilibrium point and periodic states.
    Keywords: multipartite consensus; multi-agent system; linear systems; projective parameters; adaptive control.

  • Two redundant rule-based algorithms for time-delay nonlinear models: least squares iterative and particle swarm optimisation   Order a copy of this article
    by Yuelin Xu, Yingjiao Rong 
    Abstract: Two redundant rule-based methods are developed for a time-delay nonlinear model in this paper. By using the redundant rule, the time-delay nonlinear model can be turned into a redundant model that contains some redundant terms. Then the least squares iterative and the particle swarm optimisation algorithms are applied to update the parameters and the corresponding time-delay. Compared with the redundant rule-based least squares iterative algorithm, the redundant rule-based particle swarm optimisation algorithm is more efficient for nonlinear models with complex structures. A simulation example shows that the proposed algorithms are effective.
    Keywords: nonlinear model; particle swarm optimisation algorithm; time-delay parameter estimation; redundant rule; least squares iterative.

  • Modelling and compensation of temperature errors for articulated arm coordinate measuring machines   Order a copy of this article
    by Guanbin Gao, Wenjin Ma, Jing Na, Fei Liu 
    Abstract: Different from the traditional coordinate measuring machines which are generally used in a constant temperature room, the articulated arm coordinate measuring machine (AACMM) is used in industrial sites. Hence, the temperature variation is an important factor affecting the accuracy of AACMMs, and thermal deformation error modelling and compensation play an important role in improving the measuring accuracy of AACMMs. This paper addresses the modelling and compensation of temperature errors in the AACMM. Firstly, a temperature field model of AACMMs is established by finite element analysis, based on which the influence of temperature change on single-point repeatability accuracy and spatial distance measuring accuracy for AACMMs is analysed. The results of the analysis show that non-zero linear parameters of AACMMs are influenced by temperature variation greatly, while the angular parameters are almost unchanged. Furthermore, the spatial distance measuring accuracy of AACMMs is changed significantly rather than the repeatability when the temperature varies. Then, a temperature scaling method is proposed to improve the spatial distance measuring accuracy of AACMMs, and a linear regression temperature error compensation model is established under the simulation environment. Finally, the experimental research is carried out, and the results show that in the presence of temperature scaling method, the average absolute value of distance measuring accuracy is improved by 65.24%.
    Keywords: articulated arm coordinate measuring machine; repeatability; spatial distance measuring accuracy; error compensation; temperature compensation; finite element analysis.

  • Robust control with an anti-windup technique based in relaxed LMI conditions for LTV system   Order a copy of this article
    by Rosana Rego, Marcus Costa 
    Abstract: This paper proposes a new technique to address the anti-windup (AW) with a model predictive control (MPC) scheme for linear time-varying (LTV) systems. The design problem of the AW compensator is reduced to a linear matrix inequality optimisation problem with relaxation. The main advantage of this new approach is the reduced conservativeness compared with other well-known AW techniques and to prevent integration windup in MPC controllers when the actuators are saturated. The control with AW is applied in the polytope modelling of a three-state switching cell (3SSC) DC-DC converter operating under saturation conditions in the control signal to avoid the overlapping effect. The MPC with proposed anti-windup is compared with the MPC technique and with MPC-AW without relaxation. The MPC-AW with relaxation improves the performance when the converter is operated in the saturated mode and allows the rational use of the converter, preventing the saturation from damaging its performance in a permanent regime. The simulation results validated the efficiency of the proposed approach and showed that the relaxation approach not only allows working better with the polytope modelling but also improves the response under LTV disturbance.
    Keywords: anti-windup; model predictive control; boost converter; linear time-varying systems; linear matrix inequalities.

  • Automatic regrouping of trajectories based on classification and regression tree   Order a copy of this article
    by Ying Zhang, Chenguang Yang 
    Abstract: Decomposing complex tasks into simple sub-trajectories can greatly reduce the difficulty of modelling and generalisation. Using dynamic movement primitive (DMP) to generalise these sub-trajectories and combining the generalised sub-trajectories in a different order can generalise the original task to a new task, which greatly improves the generalisation ability of DMP. In previous work, we manually determined the recombination order of trajectories, but this method was inefficient and time-consuming. Here, we automate the procedure with the decision tree approach. First, we use some known decision results as prior information to generate decision trees. Then, we input the starting and ending coordinates of each sub-trajectory of the new task into the decision tree. The decision tree will make decisions based on the coordinate information and choose which kind of trajectory to generalise to realise the new task. Simulation results are used to verify the effectiveness of the proposed method.
    Keywords: dynamic movement primitive; trajectory segmentation; classification and regression tree.

  • An iterative defogging algorithm based on pixel-level atmospheric light map   Order a copy of this article
    by Di Fan, Xiao Lu, Xiaoxin Liu, Wanda Chi, Shicai Liu 
    Abstract: Most defogging algorithms often lead to the problem of sky oversaturation and non-sky brightness. In order to solve these problems, a dark channel iterative demisting algorithm based on pixel level atmospheric light map is proposed in this paper. Firstly, the algorithm in this paper obtains a pixel-level atmospheric light map based on the model of the relationship between fog density and depth of field. Secondly, the algorithm uses an iterative defogging method to control the optimal defogging degree, thereby restoring high-quality defogging images. The experimental results show that the image obtained by the algorithm in this paper is not only high in definition but also real-time, and the problems of sky oversaturation and non-sky brightness are effectively solved.
    Keywords: image defogging; pixel-level; atmospheric light map; real-time; iterative defogging algorithm.

  • Radial basis function neural network observer based adaptive feedback control for the ABS system under parametric uncertainties and modelling errors   Order a copy of this article
    by Hamou Ait Abbas, Abdelhamid Rabhi, Mohamed Belkheiri 
    Abstract: An anti-lock braking (ABS) scheme control is a relatively difficult task owing to its highly uncertain nonlinear dynamics and the time-varying nature of the parameters. According to the requirement that the braking process must be fast and robust, we contribute in the current paper to extend the universal function approximation property of the radial basis function (RBF) neural network (NN) to design (a) an adaptive NN observer to estimate derivatives of the tracking error dynamics since the availability of the ABS model is not always practical, and (b) an robust NN output feedback controller that overcomes successfully parametric variations and uncertainties in order to address the tracking probem with bounded errors. Notice that the feedback linearisation control is introduced to linearise the ABS nonlinear system, and the dynamic compensator is involved to stabilise. The estimated states are used as inputs to the NN and in the adaptation laws as an error signal. The stability of the proposed controller in the sense of Lyapunov guarantees boundedness of both tracking errors, and estimating errors of the closed-loop system. Simulations of the proposed control algorithm based adaptive RBFNN observer are conducted then compared with the bang-bang controller to demonstrate its practical potential. Furthermore, both feasibility and efficiency have been successfully confirmed through robustness tests.
    Keywords: antilock braking system; parametric variations; unmodelled dynamics; radial basis function neural network; adaptive observer; robustness test.

  • Defect feature extraction and recognition of buried pipeline based on metal magnetic memory   Order a copy of this article
    by Yong Yang, Guan-Jun Wang, Yu Wang, Yong Wan, Yong-Shou Dai 
    Abstract: The surfaces of metal pipelines are always susceptible to various types of defect and damage, including corrosion defects and early stress concentration defects. Metal magnetic memory detection technology is the only non-destructive testing technology that can diagnose the early damage of ferromagnetic components. However, the metal magnetic memory original signal itself cannot directly recognise and distinguish corrosion defects and stress concentration defects. To solve this problem, this paper establishes a multi-characteristic statistical recognition method for the two defect types based on the metal magnetic memory technology and the magnetic memory test data obtained from pipeline test pieces. Next, this method is used to identify the defect types of four pipelines in the oilfield environment; the results demonstrate that the established defect type recognition method is effective for the identification of pipeline corrosion defects and early stress concentration defects. Because the recognition rate of the proposed method is high enough, the results of this study can provide a certain reference for the research in this field, and the proposed method has satisfactory practical application value.
    Keywords: metal magnetic memory; pipeline defects; corrosion defects; stress concentration defects; defect type recognition.

  • Machine vision based edge detection method for toilet seats   Order a copy of this article
    by Bingyan Cui, Peng Chen, Weicun Zhang 
    Abstract: When the grinding manipulator performs the task of grinding the edges of sanitary ceramics, there are problems of insufficient precision of the grinding path and insufficient stability of the grinding process. As an important module in robot control, trajectory planning plays a vital role in the stability and accuracy of the robot when working. Using the edge detection principle of machine vision for trajectory planning can provide high reliability for polishing the robot. Grinding the trajectory is more stable when grinding the edges of sanitary ceramics and can make the manipulator get rid of the harm caused by the strange posture and excessive working amplitude. According to the practical application characteristics of the toilet seat trimming process, this article proposes a new method of toilet seat edge detection. When there is a reflective area for edge detection, the method can eliminate the false edge of the image caused by the reflection. There are high precision and strong robustness in this new edge detection algorithm, which has a high guiding significance to assist the toilet seat processing industry.
    Keywords: machine vision; edge detection; toilet seats.

  • Robust design of proportional integral controllers: a Taguchi-grey approach   Order a copy of this article
    by Vinayambika S. Bhat, Shreeranga Bhat, E.V. Gijo 
    Abstract: The objective of this article is to apply and delineate a statistical approach for a robust design to determine the optimum levels of Proportional Integral (PI) controllers by considering the noise parameters in the control engineering arena. Taguchis robust engineering methodology along with Grey Relational Analysis (GRA) methodology is used for multi-objective optimisation of the process parameters. Taguchi method is effectively applied to ensure robustness of the controller designed under the set range of model parameter uncertainties, which cause undesirable variation in the performance of the PI controller. The ascertained optimal parameters from the Taguchi-grey approach are subjected to simulation analysis in the MATLAB/Simulink environment to analyse the settling time and performance indices. During the study, it is reconfirmed that the application of statistical tools assists in developing a robust controller design in a structured manner. Moreover, it is observed that the approach helps in multi-objective optimisation by accommodating both control and noise parameters in the control system design. The article presents a step-by-step approach in designing a robust controller through statistical tools. There is a gap in the academic literature regarding the application of a statistical approach in the robust design of PI controllers with specific attention to multi-objective optimisation. The article fulfils this void by systematically delineating the approach with both noise and control parameters.
    Keywords: robust design; PI controller; performance index; Taguchi method; grey relational analysis.

  • Developments on robust parallel compensator design and its possible applications   Order a copy of this article
    by Mingcong Deng 
    Abstract: A plant can be robustly stabilised via a static output feedback (SOF). However, for most real plants, sufficient conditions concerning the existence of such a static output feedback are not satisfied. Implementing a robust parallel compensator (RPC) on the plant is a good way to solve the problem. This paper investigates the developments on RPC design and its possible applications.
    Keywords: static output feedback; robust parallel compensator; uncertain plants.

  • Hinf filtering for a class of networked control systems with redundant channels subject to randomly occurring packet dropouts and cyber attacks   Order a copy of this article
    by Shuai Yin, Xiuying Li, Xianghua Ma, Kaitian Cao 
    Abstract: The problem of Hinf filter design is investigated for networked control systems subject to cyber attacks, which occur in a random way during the data transmission. The unavoidable packet dropout with uncertain expectation is considered, and the redundant channel is equipped to enhance the system performance by increasing the received data. A full-order filter is designed by means of the parameter-dependent Lyapunov function method, such that the corresponding filtering error dynamics is stochastically stable in the mean square with a prescribed Hinf disturbance attenuation level. The desired filter parameters are obtained via the linear matrix inequality technique. The vehicle suspension system is presented as an example to show the effectiveness of the proposed algorithm.
    Keywords: Hinf filter; cyber attacks; redundant channels; uncertain rates of packet dropouts; parameter-dependent Lyapunov function.

  • A fast robust template matching method based on feature points   Order a copy of this article
    by Shibing Yu, Xinli Xu, Zhen Jiang, Meihe Wang, Zhengze Li 
    Abstract: A method for template matching based on the feature matches between a target image and the template is proposed. Firstly, two sets of feature points from two images were extracted by ORB algorithm, and then the key points were matched to get a number of matching point pairs. Secondly, the wrong matches were removed to leverage feature numbers to improve quality. Finally, a grid framework was explored to locate the target object. Experiments demonstrated the great performance of the method.
    Keywords: template matching; feature points; ORB algorithm; leverage feature; motion statics model.

  • A novel approach to identify regional fault of urban power grid based on collective anomaly detection   Order a copy of this article
    by Xiaodi Huang, Minglun Ren 
    Abstract: Aiming to enhance the detection ability of regional fault in urban power grid, this paper proposes a novel detection approach based on collective anomaly detection and designs a fixed point iteration based multi-layers clustering (FPIML-clustering) algorithm. Firstly, based on abnormal signals received in urban power grid, multi-layered clustering is carried out by taking the upstream base station information of different energy levels of these abnormal points as the metric. Besides, fixed point iteration is introduced to accelerate the convergence rate. Secondly, according to different judgement rules, collective anomalies implicating the initial stage of regional faults can be identified by comparing the cluster information of the same layer as well as the upper and lower layers. The algorithm is tested on the power grid operation data of a Chinese city. The results demonstrate that the proposed approach can be used to detect potential regional faults before they reveal obvious fault characteristics.
    Keywords: urban power grid; regional fault; collective anomaly; multi-layered clustering; fixed point iteration.

  • Fault diagnosis for actuators of an intensified multifunctional Heat-Exchanger from the view of both plant and component levels   Order a copy of this article
    by Mei Zhang, Ze-tao Li, Qin-mu Wu, Boutaib Dahhou 
    Abstract: This paper proposes a FDD approach to the nonlinear model of the intensified heat exchanger system locally and globally. It implements the optimal performances monitoring on both internal dynamics of each component and the global system. The fault detection and diagnosis (FDD) of actuator is triggered once faults occur. The cause and effect relationship between unexpected temperature behaviour and internal variables of the faulty control valves is investigated. Simulations are considered to confirm the effectiveness of the proposed strategy.
    Keywords: fault diagnosis; control valve; intensified process; local fault filter; global performance monitoring.

  • Adaptive combination synchronisation of unknown chaotic Lorenz, L   Order a copy of this article
    by Mohammad Mossa Al-Sawalha 
    Abstract: In chaotic secure communication systems, the complexity of the chaotic career signal strengthens the security of the information signal. This article studies the adaptive combined synchronisation (ACS) for a class of different unknown chaotic systems. In this scheme, a combination of different states of the drive systems asymptotically synchronises with the desired states of the response system. Hence, the complexity of the communication channel is increased in secret communications. The Lyapunov stability theory proves the asymptotic stability of the closed-loop system at the origin. The design of a suitable adaptive controller ensures the target synchronisation. This work provides parameter update laws that estimate the true values of unknown parameters. This paper also presents two numerical examples of different unknown chaotic systems and simulation results that validate the efficiency and performance of the proposed ACS strategy. The presented ACS approach can be applied to multiple synchronisation strategies. The paper suggests some future problems related to this work.
    Keywords: combined synchronisation; Lyapunov stability theory; adaptive control technique; chaotic systems.

  • Fractional order active disturbance rejection control for trajectory tracking for a 4-DOF serial link manipulator   Order a copy of this article
    by Raouf Fareh, Mahmoud A. Y. Abdallah 
    Abstract: This paper presents a Fractional Order Active Disturbance Rejection Control (FOADRC) for a 4-DOF serial link manipulator to track a desired path in the Cartesian space and to ensure the stability of the tracking error. The Active Disturbance Rejection Control (ADRC) is known as a good technique to estimate the total disturbance from the dynamic model of the system and the external disturbances from the environment surrounding the robot and compensate them through suitable feedback control. This work takes advantage of the ADRC and the fractional-order controller to control the robot manipulator. The proposed control strategy has three main phases. First, converting the Cartesian space trajectory to joint space through the inverse kinematic process. Second, the FOARDC is developed to ensure good tracking in the joint space. The FOADRC uses the Extended State Observer (ESO) to estimate the total disturbances and the fractional-order PD as a feedback controller. Finally, the forward kinematic process is used to convert the real joint space trajectory into Cartesian space coordination. This proposed FOADRC is compared with the traditional ADRC to show the effectiveness of the proposed control strategy. Experimental results show that the FOADRC has better performance in terms of stability and error minimisation than the traditional ADRC.
    Keywords: FOADRC; serial link manipulator; ESO; dynamics; kinematics; stability; trajectory; MICO robot.

  • Polluted gas quantitative detection in a multi-gas sensor based on bidirectional long-short term memory network   Order a copy of this article
    by Jiangying Liu 
    Abstract: Quantitative detection of polluted gas by an electronic nose can reduce the cost of detection and improve the effciency of measurement. Through the effective pattern recognition method, the electronic nose can analyse the continuous periodic data and realise the detection of specific tasks. In this paper, pollution gas concentration prediction method based on bidirectional long-short term memory network (Bi-LSTM) is proposed. The effect of the Bi-LSTM model with different time steps, hidden layers and different combinations of sensor features on the performance of pollution gas prediction model is investigated. This method can extract deep features by automatically learning the gas response information of the sensor array, and its performance is better. The proposed method is verified on an air quality dataset, which proves that the proposed method has high accuracy in the quantitative detection of gas concentration based on electronic nose information.
    Keywords: quantitative detection; electronic nose; pattern recognition; pollution gas; bidirectional long-short term memory network.

  • Influence of some critical parameters on the stability of reaction fronts in liquid medium   Order a copy of this article
    by Hamza Rouah, Loubna Salhi, Ahmed Taik 
    Abstract: In this paper, we are interested to study the influence of some critical parameters on thermal frontal polymerisation in two cases: the first one where the monomer and the polymer are both in the liquid phase, and the second one when the monomer is liquid and the polymer is solid. The governing equations consist of coupling the Navier-Stokes equation to two convection-diffusion-reaction equations for the temperature and depth of conversion under the Boussinesq approximation. A formal asymptotic analysis is performed based on the Zeldovich and Frank-Kamenetskii approach to obtain an approximate interface problem in either case. The linear stability analysis is investigated to study the resulting interface models for both cases. The obtained dispersion relations of both cases are solved numerically, and then the stability conditions of the reaction fronts are found according to the different critical parameters of the problem considered. The instability conditions obtained are in good agreement with some previous studies.
    Keywords: frontal polymerisation; reaction fronts; Boussinesq approximation; Lewis number; stability analysis.

  • Adaptive parameter identification of lithium-ion batteries with adaptive linear neuron and state-of-charge estimation based on open circuit voltage   Order a copy of this article
    by Ghania Aggoun, Djaffar Ould Abdeslam, Rachid Mansouri 
    Abstract: The state of charge (SOC) is a critical parameter of a lithium ion battery. An accurate online estimation of the SOC is important for forecasting the electric vehicle driving range. A good estimation of the SOC results from a good identification of the battery parameters. Reducing the algorithm complexity is important to improve the accuracy of SOC estimation results. We propose in this work an original structure of an ADALINE (ADAptive LInear NEuron) to estimate the SOC. The ADALINE provides the weighted sum of the inputs, based on an online identification of the open-circuit voltage (OCV). The advantage of this approach is its adaptable capability and the speed of execution (fast training) as well as the possibility of interpreting these weights. The simulation results indicate that the proposed method can ensure an acceptable accuracy of SOC estimation for online application with a maximum error being less than 5%.
    Keywords: state-of-charge; equivalent circuit model; parameter identification; adaptive linear neuron; state observer design; open circuit voltage.

  • Performance enhancements of physical systems by reduced-order modelling and simulation   Order a copy of this article
    by Amit Kumar Manocha, Ankur Gupta 
    Abstract: It is a matter of great concern these days to simplify large-scale physical systems for obtaining a better understanding of the behaviour more accurately at a faster rate. Model order reduction techniques are used for simplification of the complex large-scale physical systems. This paper focuses on the designing of a method of model order reduction based on the mixed approach. The proposed method is designed by a combination of improved pole clustering to reduce the denominator and a genetic algorithm to reduce the numerator equation. The model order reduction technique proposed is compared with previously designed methods of model order reduction. These techniques are implemented in MATLAB simulation environment. The performance comparison is made based on the calculated parameters, viz. integral square error (ISE), rise time, percentage overshoot, steady-state error, and settling time for a real-time physical process. The stability of the reduced order model obtained from the proposed method is also checked by the value of gain margin and phase margin. The research work reveals that the proposed method provides an improved approximation of a large order system, as compared with previous techniques, with less error, improved accuracy and better transient and steady-state response.
    Keywords: balanced truncation; clustering; dominant pole retention; genetic algorithm; mixed approach; order reduction; physical system.

  • Natural gas engine model for speed and air-fuel control   Order a copy of this article
    by Yi Han, Peter Young 
    Abstract: With the low price of natural gas, and its low emissions, significant market growth for natural gas engines is likely in various applications. There are multiple challenges in controlling a natural gas engine, especially a pre-mixed lean burn natural gas engine. In particular, the system dynamics includes long fuel and air transport delays. In terms of natural gas engine control, our main focus is on engine speed control, engine output torque control, air/fuel ratio and emission regulation. In order to facilitate control study and development, we develop a control-oriented turbocharged pre-mixed lean burn natural gas engine mean value model. This model is designated for natural gas engine controller design, control algorithm development, and first step validation. The model is implemented in the MATLAB Simulink environment. The model is validated with a 10 L natural gas engine for power generation applications.
    Keywords: modelling; control systems; natural gas; internal combustion engine.

  • Displacement velocity control of a mechanised welding system by low-cost state feedback controller   Order a copy of this article
    by Andreyna Sárila Ramos Ferreira, Débora Debiaze De Paula, Paulo Jefferson Dias De Oliveira Evald, Rodrigo Zelir Azzolin 
    Abstract: Since welding is one of the most harmful activities in industry, robots and mechanised systems in this process are widely used. As a result, researches about autonomous and semi-autonomous welding systems have an important rule to reduce losses and improve welding quality. This work contributes to the velocity control of the displacement module of a linear semi-autonomous welding mechanised system. We propose to use a Pole Placement Control (PPC), which has a simple structure state feedback controller based on poles allocation, which can be applied on low-cost control platforms and use a reduced set of sensors. Experimental results, tested on a Bug-O Modular Drive System Linear Weaver, are presented to discuss the feasibility of the proposed control strategy.
    Keywords: state feedback control; pole placement control; poles allocation; linear welding robot.

  • Self-tuning fuzzy logic PID controller with a practical view to PEM fuel cell air supply system   Order a copy of this article
    by Mehdi Rakhtala 
    Abstract: The polymer electrolyte membrane fuel cell (PEMFC) is an appropriate candidate in renewable energy resources to using in vehicular, industrial and other applications. This research paper concentrates on the nonlinear model of the PEMFC system. The load fluctuations in the fuel cell stack affect the lifetime and cause fuel cell stack damage and ageing. So, a closed-loop control system is suggested to regulate the oxygen excess ratio at the desired value. In this paper, a self-tuning fuzzy logic PID (FPID) controller is suggested for an PEMFC air supply system because the fuel cell is a very severely nonlinear system. The oxygen excess ratio is regulated to a desired value by adjusting the air flow-rate. The control scope is to adjust the oxygen excess ratio in its operating range by controlling the compressor. The proposed FPID controller is a nonlinear and robust controller that ensures good efficiency around each equilibrium point under model uncertainties and avoids oxygen starvation during load fluctuations.
    Keywords: PEMFC; self-tuning; fuzzy logic PID; oxygen excess ratio; durability.

  • Robust energy-to-peak control for Markov jump system with multiple pure time delays   Order a copy of this article
    by Falu Weng, Huan Wang, Yuanchun Ding 
    Abstract: This paper investigates the robust energy-to-peak stability analysis and controller design for the Markov jump system with multiple pure time delays. The aim is to get some sufficient conditions such that the controlled system is asymptotically stable with a anti-disturbance performance. Firstly, according to the system transformation, the Markov jump multiple pure time delays system is transformed into a new description, which includes a non-time-delay item and some integral items. Secondly, according to Lyapunov stability theory and LMI technique, the sufficient theorems are achieved for the Markov jump multiple pure time delays system to have energy-to-peak stability and stabilisation. If those theorems are solvable, controllers can be obtained such that the controlled systems are stable and the peak values of the controlled outputs are constrained for any energy-bounded external disturbance inputs. Moreover, the uncertain cases are considered, and the robust stability conditions are achieved. Finally, examples are given, and the effectiveness of the obtained methods is illustrated.
    Keywords: pure multiple time delays; Markov jump; LMI; energy-to-peak control; uncertainty.

  • Nonlinear control and energy management of the hybrid fuel cell and battery power system   Order a copy of this article
    by Hassan El Fadil, Zakariae El Idrissi, Abdessamad Intidam, Aziz Rachid, Mohamed Koundi, Tasnime Bouanou 
    Abstract: This paper deals with the problem of controlling a hybrid energy storage system, used in hybrid electric vehicles. The system consists of a PEM fuel cell and batteries as sources and two DC-DC power converters. A nonlinear controller and an energy management system (EMS) are developed. Firstly, an appropriate nonlinear model of the studied system is elaborated. Then, a nonlinear controller is elaborated using Lyapunov theory to ensure the following objectives: i) tight DC-bus voltage regulation, ii) perfect tracking of the battery current to its reference, and iii) asymptotic stability of the closed-loop system. Secondly, using Bellman's principle of optimality, the EMS is designed to generate an optimal reference signal of the battery current. The objective is to share the load power between the fuel cell and the battery minimising the hydrogen consumption. It is shown, finally, using theoretical analysis and simulations, that the objectives of the nonlinear controller and the EMS are achieved whatever the used vehicle and the traction motor. Interestingly, the only used information on the traction part is the load current.
    Keywords: fuel cell; DC-DC power converter; battery; nonlinear control; energy management system; Lyapunov theory; Bellman's principle of optimality.

  • Modelling and experimental study on hierarchical throttling water distributor   Order a copy of this article
    by Yuhai Cui, Yongqiang Kong, Rui Xia 
    Abstract: In this paper, the pressure differential hierarchical throttle distributor is taken as the research object. First, the turbulence model of the flow field inside the water distributor is established. Then, using different nozzle assembly forms, the experiment is carried out at different flow rates to obtain the pressure and speed change curves. Then, using an offset long water nozzle hollow throttle core, the water nozzle is placed in different spatial positions, and an experimental study is carried out to obtain the pressure and speed change curves, and summarise the change rules therein. Finally, according to the experimental results, suggestions for effective evaluation and parameter optimisation are proposed. The research results can play a good guiding role in the design of a large-pressure differential hierarchical throttling water distributor.
    Keywords: water distributor; flow field; experimental research; optimisation.

  • Image semantic segmentation based on improved DeepLab V3 model   Order a copy of this article
    by Haifei Si, Zhen Shi, Xingliu Hu, Yizhi Wang, Chunping Yang 
    Abstract: To improve the image-segmentation speed based on the accuracy of a convolution neural network model, an improved DeepLab V3 network is proposed in this paper. The original feature extractor of DeepLab V3 is replaced with the lightweight network structure of MobileNet V2, and the original nonlinear activation function of a rectified linear unit is partially displaced by a new Swish activation function. Experimental results show that the improved DeepLab V3 network model can balance the segmentation accuracy and speed of the model better than the V3+ algorithm, which is the most accurate DeepLab network model till now. The running speed is improved significantly with a certain level of accuracy. In tests using different datasets, the running time decreased by 84% and 88.9%, and the model memory consumption decreased by approximately 96.6%. The improved DeepLab V3 network can adapt to deep-learning applications and satisfy their high-speed requirements.
    Keywords: deep learning; DeepLab V3 model; lightweight; depth-wise separable convolution; semantic segmentation.

  • Improvement and analysis of a mechanically adapted Lofstrand crutch model through bond graph modelling   Order a copy of this article
    by Rebeca Hannah Oliveira, Danilo Dos Santos Oliveira, Andrey Negreiros Pimenta, Ludmila Evangelista Dos Santos, Giselle De Oliveira Lima, Emerson Fachin-Martins, Danielle Brasil Barros Da Silva, Jackson Paz Bizerra De Souza, José Henrique De Oliveira, Suelia De Siqueira Rodrigues Fleury Rosa 
    Abstract: Lofstrand crutches are mobility devices applied temporarily during the rehabilitation process or permanently as an assistive device. As a permanent device, they have a deep impact on the body owing to the reactive force redistributed on the upper limbs. We present a review of the development and implementation of an innovative cushioning crutch-mounting device as well as a sensorial system for gathering feedback data. We propose a bond graph mathematical model to compare the traditional Lofstrand crutches with a modified Lofstrand crutch. Through state-space equations extracted from our model, we demonstrate a reduction in the resulting force through the introduction of the damping device on the crutch system. The simulation by the mathematical models demonstrated that the cushioning might incur effective minimisations on the upper limbs force redistribution, avoiding further movement disabilities for permanent users.
    Keywords: Lofstrand crutches; adapted Lofstrand crutches; bond graph modelling; rehabilitation; crutch mounting device; force sensor resistor; mechanical damping device; assisted gait.

  • Prediction and reduction of spatial transverse vibration of hoisting catenaries induced by drum winding in super-deep mine hoists   Order a copy of this article
    by Jiannan Yao, Yansong Ma, Chi Ma, Tong Xu, Xingming Xiao 
    Abstract: Spatial transverse vibration of hoisting catenaries excited by drum winding in super-deep mine hoists may result in the catenary whirling motion, which may cause disordered rope arrangement and the rope to jump out of the sheave groove. This paper focuses on predicting and reducing the spatial transverse vibrations of hoisting catenaries induced by drum winding. Firstly, the governing equations of spatial transverse vibration of a hoisting catenary and the rope tension have been derived and experimentally validated. Subsequently, according to the structure of the rope groove on the LeBus drum, the functions of the transverse and lateral excitation displacements at the drum end and the hoisting velocity have been precisely modelled and calculated. Numerical simulation indicates that large amplitude spatial vibration will be excited by drum winding and that the quasi-static rope tension can be employed to predict the spatial transverse vibration of the catenary. Eventually, a vibration isolated system is proposed to reduce the spatial transverse vibrations of a catenary, and numerical simulation is used to validate the feasibility. The paper will provide good technical support for the vibration suppression of hoisting catenaries in super-deep mine hoists.
    Keywords: super-deep mine hoist; catenary; spatial transverse vibration; vibration isolated system; vibration suppression.

  • Design and control of a bidirectional active balancing model for a lithium-ion battery pack   Order a copy of this article
    by Qiuting Wang, Wei Qi 
    Abstract: The performance of single cell and serial/parallel lithium-ion battery pack can be inconsistent, owing to deviation of the production process and the difference of application environment. It will easily lead to the decline of the overall capacity of the battery pack. In our study, an efficient bidirectional active balancing strategy based on duty ratio is proposed. The optimal solution of voltage value is obtained in each equalisation cycle. A model predictive control (MPC) algorithm is established to balance the SOC value of each cell. The bidirectional DC/DC converter is designed to transfer the energy between one cell and its adjacent cell. The experimental results indicate that our new model and balancing strategy can effectively reduce the voltage difference between different cells. It can overcome the shortcomings of traditional balancing strategies, such as low energy transfer efficiency, long equalisation time and unsuitability for large capacity battery packs. Besides, it avoids unnecessary energy transfer and reduces the balancing time by 31%.
    Keywords: lithium-ion battery; serial/parallel pack; bidirectional balancing circuit; predictive control; DC/DC converter; SOC.

  • Cooperative spectrum prediction algorithm based on overlapping alliance game   Order a copy of this article
    by Xin Wang, Wei Li, Yongfeng Chen, Li Dai 
    Abstract: In order to solve the problem of unsatisfactory accuracy of spectrum prediction in a network with multiple primary users, this paper proposes a cooperative spectrum prediction algorithm. The overlapping alliance game is introduced into spectrum prediction. The alliance structure with the highest accuracy of collaborative prediction is selected, and the result with the highest accuracy is obtained. In the experiment, three different collaborative prediction methods are compared and the effects of different parameter values on the simulation results are analysed. The results show that the proposed method has high prediction accuracy, adaptability and robustness.
    Keywords: spectrum prediction; cooperative spectrum prediction algorithm; overlapping alliance game.

  • Adaptive cubature quadrature filter for nonlinear state estimation   Order a copy of this article
    by Aritro Dey 
    Abstract: A new filtering algorithm is proposed for nonlinear state estimation where the measurement vector is a nonlinear function of system states and measurement noise. The proposed adaptive cubature quadrature filter demonstrably presents improved estimation performance in the situation where the measurement noise covariance remains unknown to the designer. The filter has been designed based on Bayesian filtering framework with cubature quadrature rule for approximation of Gaussian integral, and also incorporates an adaptation algorithm designed for auto-tuning of unknown measurement noise covariance. The adaptation algorithm, theoretically developed following Maximum Likelihood Estimation (MLE) for non-additive noise, is numerically stable as it secures the positive definiteness of adapted measurement noise covariance. The superiority of the proposed filter is demonstrated in simulation over its non-adaptive counterpart and the competing algorithms of adaptive nonlinear filters, with the help of some non-trivial case studies. Additionally, suitability of the proposed algorithm is validated for non-stationary measurement noise.
    Keywords: adaptation; cubature quadrature filter; maximum likelihood estimation; measurement noise covariance; non-additive noise; nonlinear filtering.

  • Distinguishability study of three-mass models for electromechanical motion systems   Order a copy of this article
    by Mathias Tantau, Christian Helmke, Lars Perner, Mark Wielitzka 
    Abstract: Physically motivated models of electromechanical motion systems are required in several applications related to control design and auto-tracking, model-based fault detection, feed-forward, and simply interpretation. However, attempts to create such models automatically via structure and parameter identification struggle with ambiguities regarding the correct internal structure of the model. Designing a reasonable set of candidate models is difficult, because it is not known which models are distinguishable and which are not. This paper gives a simple-to-use necessary condition for indistinguishability of multiple mass models as they are used to model the control-relevant features of motion systems. In an automated way, models are generated that can be created by considering elasticities at different positions in the mechanical structures. The condition is applied to these models for the case of three masses. In three examples it is shown that the criterion simplifies the subsequent structure and parameter identification considerably by reducing the number of possible models. For higher numbers of masses, however, it would become intractable.
    Keywords: indistinguishability analysis; multiple mass resonators; multiple mass models; electric drive trains; electromechanical motion systems; servo control systems; structure and parameter identification; model selection; model structure optimisation; transfer function type; poles and zeros; frequency domain; frequency response function.

  • Several structure pool based identification algorithms for ARX models: order and parameter estimation   Order a copy of this article
    by Jianwei Lu 
    Abstract: Several structure pool based identification algorithms are proposed for ARX models with unknown order in this study. Since the order of the ARX model is unknown, a structure pool that contains various different information products is provided, and then the gradient iterative and two-direction stochastic gradient algorithms are provided to estimate the order and the unknown parameters simultaneously. The proposed algorithms can be applied for systems with unknown orders and parameters, thus are more promising in engineering practice. A simulation example is used to validate the efficiency of the proposed algorithms.
    Keywords: order identification; gradient iterative algorithm; ARX model; two-direction stochastic gradient algorithm; parameter estimation; structure pool.

  • Disturbance rejection for a quadrotor using robust active force control with genetic algorithm   Order a copy of this article
    by Sherif I. Abdelmaksoud, Musa Mailah, Ayman M. Abdallah 
    Abstract: Among the various types of rotorcraft unmanned aerial vehicles (UAVs), the quadrotor is currently one of the most versatile flying machines. However, it is an under-actuated, highly non-linear coupling system. It is also sensitive to external disturbances and uncertainties while tracking certain paths, which can affect its performance and may cause undesirable movements that sometimes lead to the failure of the entire system. This work introduces an innovative hybrid control scheme for a quadrotor model to reject different forms of external disturbances while ensuring stability during trajectory tracking. The proposed control structure incorporates an active force control (AFC) strategy with a proportional-integral-derivative (PID) controller, tuned using the genetic algorithm (GA) method, known as the (PID-AFC-GA) scheme. In addition, a sensitivity analysis of the effect of using the partial-to-total output of the AFC signal was investigated. The hybrid PID-AFC-GA controller gives better disturbance rejection efficacy than the other proposed methods.
    Keywords: quadrotor control; Newton-Euler method; active force control; PID controller; genetic algorithm optimisation; disturbance rejection; trajectory tracking.

  • Frequency characteristics of a phase-optimised active disturbance rejection control   Order a copy of this article
    by Wei Wei, Pengfei Xia, Nan Chen, Min Zuo 
    Abstract: A linear extended state observer (LESO) can just estimate constant disturbances with no steady-state error. In order to improve the ability of an extended state observer (ESO) to estimate time-varying disturbances, a phase optimisation law (POL), which is of simple structure and easy to realise, is proposed. Based on the POL, both a phase-optimised extended state observer (POESO) and a phase-optimised active disturbance rejection control (POADRC) are proposed. Before and after introducing the POL, estimation errors, estimation phases, and ability of the ESO to estimate the total disturbance are analysed and compared. Results show that the estimated phase of the POESO is always ahead of the one of a LESO, and a POESO is able to estimate slope disturbances with zero steady-state error. Transfer functions of tracking, total disturbance and noise are also obtained. The ability of the active disturbance rejection control to cancel out the total disturbance or suppress noise, and stable regions in presence of the uncertain control gain and parameter are analysed and compared. Both frequency analyses and numerical results show that, compared with the linear active disturbance rejection control, the POADRC can estimate the time-varying disturbances and improve the closed-loop performance more effectively.
    Keywords: active disturbance rejection control; extended state observer; frequency characteristics; optimised phase.

  • Modelling and structure optimisation on throttle tube of pre-throttle water distributor   Order a copy of this article
    by Yuhai Cui, Rui Xia, Yongqiang Kong 
    Abstract: In this paper, taking an oilfield as the research object, the pre-throttle water distributor is tested and studied. Aiming at the pre-throttle water distributor, the flow field of throttle tubes with different circles and sizes is calculated, the pressure drop and velocity are compared and analysed, and the test results are drawn. According to the test results, the optimal pipe diameter and circle number selected under different pressure drops are determined. The research results can play a good guiding role in the design of the pre-throttle water distributor.
    Keywords: water distributor; throttle tube; pressure drop; flow rate.

  • Stability for thermo-elastic Bresse system of second sound with past history and delay term   Order a copy of this article
    by Khaled Zennir, Djamel Ouchenane, Abdelbaki Choucha 
    Abstract: In the present paper, a one-dimensional linear thermo-elastic system of Bresse type with past history and delay term is considered. We prove the well-posedness of the problem using the semigroup method. By using the energy method, we discuss the stability of the system for two cases. An exponential stability result of system (ref{TR1}) is obtained in the case where the propagation velocities are equal in equation of vertical displacement and the equation of system rotation angle in eqref{en1}. Furthermore, a result of algebraic stability is obtained in the case of the different propagation velocities in eqref{en}, where the initial data $E_2(0)$ is involved in the decay rate for the case.
    Keywords: Bresse system; thermo-elastic; past history; delay; asymptotic stability; energy method; semigroup method.

  • Roll angle dynamic control of unicycle robot using backstepping controller and sliding mode Controller.   Order a copy of this article
    by Boutaina Elkinany, Mohammed Alfidi, Zakaria Chalh 
    Abstract: The unicycle robot is the most sophisticated and the newest mechanism used in the robotics industry regarding its high degree of mobility. It represents an unbalanced, non-holonomic system that can move and stand with only one wheel. Accordingly, it is the best platform for researchers to model and study stability. This paper focuses on the modelling of the unicycle robot using the Lagrangian dynamic formulation. Two nonlinear controllers are presented: the sliding mode and the backstepping controllers that were designed to control the roll angle. Both controllers were simulated and the results showed that the stabilisation of the roll angle can achieve a good performance and good robustness using the backstepping controller rather than the sliding mode controller.
    Keywords: unicycle robot; sliding mode controller; backstepping controller; stability; modelling; simulation; Lyapunov function.

  • Model predictive current control combined sliding mode speed control for PMSM drive system   Order a copy of this article
    by Qian Guo, Tianhong Pan 
    Abstract: This work deals with an improved Model Predictive Current Control Combined Sliding Mode Speed Control(SMC+MPC) method to reduce the tracking error of speed and current for permanent magnet synchronous motor (PMSM). Firstly, the establishment of the PMSM mathematical model in the synchronous rotating frame is introduced. Secondly, a cascade PMSM control system has been created. In this system, a sliding mode speed controller and a model predictive current controller are employed respectively to enhance the speed tracking accuracy and suppress the harmonic component of the three-phase currents. Finally, the schematic diagram of the proposed method and simulation results are provided. Moreover, sliding mode speed control combined with proportional-integral (PI) current control is simulated for comparison to prove the superiority of the proposed method.
    Keywords: model predictive current control; sliding mode speed control; permanent magnet synchronous motors.

  • Model predictive control for an industrial coal pulveriser   Order a copy of this article
    by Vini Dadiala, Jignesh Patel, Jayesh Barve 
    Abstract: The coal-pulveriser/coal mill is an important subsystem upstream of boilers in coal-based thermal power plants. The efficient boiler operations demand optimum combustion-air to coal-fuel ratio (AFR). In fact, a portion of (preheated) combustion air, called primary air, passes through the coal mill and carries pulverised coal to the boiler. The safe, efficient coal-mill operation is important and requires (1) safe temperature control of primary air-coal mixture inside/outlet of mill; (2) optimum primary air-to-fuel ratio (pAFR); (3) swift tracking of coal-flowrate setpoints to cater for variable power-load demands. In this paper, a multivariable Model Predictive Control (MPC) scheme is proposed for a specific industrial coal mill. Also, a simulation study is performed using a validated industrial coal-mill model, and the performance of the MPC scheme is compared with two other control schemes, industrial 2PI and prior published 3PI with selective control. The MPC outperforms the other two control schemes and provides better control performance, respects coal-mill operational constraints, and improves primary air-to-fuel ratio.
    Keywords: coal pulveriser; air-fuel ratio; model predictive control; primary air-fuel ratio; stochiometric AFR; 3PI with selective control; coal moisture; latent heat; sensible heat.

  • Computationally efficient model predictive control for quasi-Z source inverter based on Lyapunov function   Order a copy of this article
    by Minh-Khai Nguyen, Kim-Anh Nguyen, Thi-Thanh-Van Phan, Van Quang Binh Ngo 
    Abstract: This paper proposes a computationally efficient model predictive control strategy for the quasi-Z source inverter. Unlike the previous finite control set model predictive control method, besides the ability of computational cost reduction, the proposed method considers the stability of the closed-loop system in the control design. At each sampling period, only feasible switch control inputs that satisfy the stability condition derived from a control Lyapunov function are taken into account in the minimisation of the cost function. Therefore, the computation time of the optimisation problem is decreased compared with the previous algorithm. A comparison of the previous model predictive control method is investigated by Matlab software in various operating conditions of the system. The achieved results verify the benefit of the proposed approach for dealing with the stability and computational burden over the conventional method while maintaining high control performance.
    Keywords: quasi-Z source inverter; finite control set model predictive control; delay compensation; computational burden; control Lyapunov function.

  • Study on Temperature Rise and Thermal Deformation of Rotor Caused by Eddy Current Loss of Magnetic-Liquid Double Suspension Bearing
    by liwen chen, Dianrong Gao, Jianhua Zhao, Jisheng Zhao 
    Abstract: Magnetic-Liquid Double Suspension Bearing (MLDSB) is composed of electromagnetic supporting system and hydrostatic supporting system. Due to greater supporting capacity and static stiffness, it is a great choice under the occasion of middle speeds, overloading and frequent starting. As the MLDSB works, the rotor will rotate at high speed and cut the magnetic induction line to produce eddy current loss (ECL), which will increase the temperature of rotor and lead to thermal deformation. Gaps between magnetic poles and magnetic sleeve are small, so thermal deformation of rotor has a clear impact on oil film thickness, bearing capacity and operation stability. Therefore, the simulation model of MLDSB was established, and the simulation of current loss, temperature rise and thermal deformation of rotor under maximum load condition were carried out. The result showed that eddy current loss will be aggravated by the increase of coil current, number of turns of coils and rotor speed, which will cause temperature rise and thermal deformation of rotor. The research in this paper can provide the theoretical reference for ECL of MLDSB.
    Keywords: Magnetic-Liquid Double Suspension Bearing; eddy current loss; temperature rise; thermal deformation

  • Modal analysis and modelling approach for piezoelectric transducers based energy harvesting applications   Order a copy of this article
    by Nadjet Zioui, Aicha Mahmoudi 
    Abstract: Energy harvesting-based piezoelectric (PE) stress-strain has gained a huge buzz in recent years. Many academic researches and industrial efforts have been conducted in order to contribute to bringing new ways to harvest energy from mechanical machines' vibrations, road vehicles' interactions and human motion. Establishing a representative model for a system is a vital step in the process of design, control or operation of any system in engineering. This is more factual in the context of energy harvesting. A good knowledge of the harvesting element makes it possible to predict its behaviour, therefore the useful energy that can be harvested. In this paper, an assessment of the several modelling methodologies is established, with a specific focus on the dynamic behaviour of piezoelectric devices in the context of energy harvesting applications. Several papers related to the topic of modelling piezoelectric elements in the perspective of energy harvesting are presented with the purpose of discussing their forces and limitations. The paper proposes an approach of modelling the piezoelectric elements' dynamic operation. The approach considers a transfer function with parameters to be identified depending on the experimental spectral response of the element. This approach allows an enhanced comprehension of the element dynamic behaviour, including several dynamics that can possibly be omitted during the modelling process. Two cases of study are illustrated and concisely compared with the models in the literature in order to highlight the significance of specifying the validity set of the model.
    Keywords: energy harvesting; piezoelectric transducer; modal analysis; mathematical modelling; transfer function.

  • A new family of 9-D and 10-D hyperchaotic systems from the 8-D hyperchaotic Benkouider system, the bifurcation analysis of the 10-D hyperchaotic system, circuit design and an application to secure voice communication   Order a copy of this article
    by Khaled Benkouider, Toufik Bouden, Sundarapandian Vaidyanathan, Mustak E. Yalcin 
    Abstract: This work presents a new 10-D polynomial hyperchaotic system with eight positive Lyapunov exponents. We propose a family of new 9-D and 10-D hyperchaotic systems, which are derived from the 8-D hyperchaotic system (2020). With its eight positive Lyapunov exponents, the proposed 10-D hyperchaotic system generates a more complex behaviour than the existing systems, which makes it very useful in many fields of applications, especially in secure communication. Major properties of the new system are investigated using Lyapunov exponents, bifurcation diagrams, phase portraits, equilibrium points, Kaplan-Yorke dimension and multistability. In addition, an equivalent electronic circuit is implemented using Multisim software to validate the physical feasibility of the constructed 10-D hyperchaotic system. Finally, a new secure voice communication scheme is developed based on the chaotic masking approach and using all the complex hyperchaotic signals generated by the new 10-D hyperchaotic system.
    Keywords: chaos; hyperchaos; hyperchaotic systems; circuit design; secure communication.

  • Modeling of nonlinear dynamic stability in cylindrical grinding process   Order a copy of this article
    by Amon Gasagara 
    Abstract: The cylindrical grinding process is a complex phenomenon with several vibration excitation parameters that lead to oscillation of the grinding wheel and workpiece deflection. In this work, a new model of the cylindrical grinding process vibrations is developed to analyse a particular type of dynamic instability induced by the in-feed rate. The grinding wheel is modelled as a constant speed moving oscillator excited by the grinding forces to provide a time-varying excitation load to induce the workpiece deflection. The workpiece is regarded as a simply supported non-uniform Euler-Bernoulli beam. The numerical analysis is used to obtain the governing equations of the process dynamics. MATLAB is used to obtain the dynamic response of the process. The experiment is used to validate the model simulation results. The results of the tested grinding mode show that the dynamic stability of the process is benefitted at the in-feed rate of 0.01 mm/sec while reducing the grinding time.
    Keywords: cylindrical grinding process; in-feed rate; dynamic vibration response; moving oscillator; chatter vibrations.

  • An Optimal Control Approach for Hybrid Motion/Force Control of Coordinated Multiple Nonholonomic Mobile Manipulators using Neural Network
    by Komal Rani, Naveen Kumar 
    Abstract: This paper presents an intelligent optimal control approach for motion/force control of cooperative multiple nonholonomic mobile robot manipulators carrying a single rigid object. Firstly, a combined model of multiple mobile manipulators and the object is obtained in terms of object coordinates. Using this model, a state-space form of error dynamics is derived for quadratic optimization. Then, the explicit solution of Hamilton Jacobi Bellman equation (HJB) for optimal control is obtained by Riccati equation. The linear optimal control, neural network and adaptive bound are utilized to design the proposed controller. It is shown that the uncertainties of the system are compensated using radial basis function neural network and adaptive compensator. The radial basis function neural network approximates the unknown dynamics and adaptive compensator estimates the bounds on neural network approximation error and the unstructured uncertainties of the system. The asymptotical stability of the closed-loop system is demonstrated using Lyapunov stability analysis and the optimal control theory. Finally, the proposed control approach are verified in comparative manner through simulation results with two identical mobile manipulators grasping the single rigid object.
    Keywords: Multiple Mobile Manipulators; Optimal Control; Hamilton Jacobi Bellman Optimization(HJB); Motion/Force Control; RBF Neural Network; Adaptive Compensator; Asymptotical stability.

  • Differentially flat trajectory generation and controller design for a quadrotor UAV   Order a copy of this article
    by Arindam Singha, Anjan Kumar Ray, Arun Baran Samaddar 
    Abstract: A control strategy of differentially flat trajectory generation and a backstepping controller for tracking the desired trajectory are developed for a quadrotor Unmanned Aerial Vehicle (UAV). A globally smooth trajectory is generated through multiple waypoints, which are at different planes. To show the effectiveness of the trajectory generation method, four different shapes of trajectories are generated using different numbers of waypoints. Simulation studies have shown that the proposed paradigm is able to generate smooth trajectories using multiple waypoints. Along with that, the quadrotor UAV has successfully tracked the desired trajectories by using the proposed controller. The proposed controller is also validated with constant and variable desired yaw angles. The robustness of the proposed controller is validated in the presence of external disturbances in the system control input. The proposed controller is also compared with other controllers and shows satisfactory performances.
    Keywords: Andrews' curve; backstepping controller; differential flatness; trajectory generation; trajectory tracking; quadrotor UAV.

  • Modified Augmented Fractional Order Control Schemes for Cart Inverted Pendulum Using Constrained Luus-Jaakola Optimization
    by DEEP MUKHERJEE, G.LLOYED RAJA, PALASH KUNDU, APURBA GHOSH 
    Abstract: Since the upright position of an inverted pendulum system is an unstable equilibrium, it is extremely challenging to control. Fractional order based control schemes are becoming increasingly popular in stabilizing an unstable system and achieving satisfactory closed-loop performance. Therefore, a novel combination of fractional order Lyapunov (FOLyapunov) rule and fractional order proportional integral (FOPI)/ two-degree of freedom FOPI (2DOF-FOPI) controller is proposed to tackle this problem. Parameters of FOPI/2DOF-FOPI controllers are obtained using multi-objective constrained Luus-Jaakola multipass optimization method. Comparative simulation studies are carried out with direct synthesis based PID control scheme, combination of fractional order Massachusetts Institute of Technology(FOMIT) rule augmented with either FOPI/2DOF-FOPI controllers using a mathematical model of inverted pendulum. It is evident that the proposed combination of FOLyapunov method and FOPI/2DOF-FOPI controllers outperforms the other schemes.
    Keywords: Inverted pendulum; MRAC; Fractional calculus; MIT rule; FOMIT rule; FOPI; 2DOF-FOPI; Luus-Jaakola algorithm; FOLyapunov stability rule

  • H model reduction of discrete-time 2D T-S fuzzy systems in finite frequency ranges   Order a copy of this article
    by Abderrahim El-Amrani 
    Abstract: This paper deals with the problem of H model reduction for two-dimensional (2D) discrete Takagi-Sugeno (T-S) fuzzy systems described by the Fornasini-Marchesini local state-space (FM LSS) model, over finite frequency (FF) domain. The problem to be solved in the paper is to find a reduced-order model such that the approximation error system is asymptotically stable, which is able to approximate the original T-S fuzzy system with comparatively small and minimised H performance when frequency ranges of noises are known beforehand. Via the use of the generalised Kalman Yakubovich Popov (gKYP) lemma, new design conditions guaranteeing the FF H model reduction are established in terms of linear matrix inequalities. To highlight the effectiveness of the proposed H model reduction design, a numerical example is given.
    Keywords: multidimensional systems; finite frequency H∞; model reduction; T-S fuzzy systems.

  • Social spider optimisation based identification and optimal control of fractional order system   Order a copy of this article
    by Sandip Mehta, Dipak Adhyaru 
    Abstract: Fractional order derivatives and integrals are infinite-dimensional operators and non-local in time. Currently, the researchers are working on the solution of the fractional optimal control problem using some approximation and numerical analysis. In this paper, a social spider-based constrained optimisation method is proposed to control the fractional order system. An effort has been made to translate the fractional optimal control problem to the standard unity feedback system. A multi Simpson method has been used to solve the integration of the performance function. The proposed method has not used any matrix computation and it has been demonstrated that it is easier to implement the FOCP (fractional order optimal control) method on the given hardware. Along with the optimal control, a simple identification technique is proposed for the fractional order system. The optimal controller has been designed using computational intelligence techniques. The error analysis and the performance analysis have been carried out for the proposed methods.
    Keywords: fractional order system; SSO-C; FOCP; metaheuristic algorithms.

  • Optimal fractional order control for nonlinear systems represented by the Euler-Lagrange formulation   Order a copy of this article
    by Ahmad Taher Azar, Fernando E. Serrano, Nashwa Ahmad Kamal 
    Abstract: In this paper, a novel control strategy is shown for the control of fractional order systems established in the Euler-Lagrange formulation. This strategy is based on the design of an optimal controller considering a fractional order system based in the Euler-Lagrange formulation because this allows more degrees of freedom in the system establishment and the optimal controller design. The design procedure consists of establishing a performance index and then, by finding the gradient of this index, an optimal control law is obtained with the initial and final conditions of the system. It is important to note that there are a limited number of studies related to this topic found in the literature. Finally, in order to test the theoretical results obtained in this work, a numerical example that consists of the stabilisation of a two-links robotic manipulator is shown.
    Keywords: optimal fractional order control; fractional order systems; optimal control; Lagrangian systems.

  • Feature pair pyramid detector for small product defect detection   Order a copy of this article
    by Zihao Huang, Hong Xiao, Tao Wang, Junhao Zhou 
    Abstract: There are many object detection algorithms that have performed well on public datasets, and they can be used in product defect detection. But there are still many details, which can affect the detection performance of actual product defect detection, that need to be optimised. In this paper, we design a defect detector, called feature pair pyramid (FPP) detector, and optimise it for specific industrial application using three methods. Then we use FPP detector to detect defects of metal can products of an enterprise. The experiment results show that our FPP detector is more effective in detecting small size defects. The performance (AP@0.5) of our detector is better than current state-of-the-art detectors.
    Keywords: defect detection; small object detection; feature pair pyramid; one-stage object detector; Resnet; k-means; anchor box.

  • Assessing the feasibility of underwater vehicle controllers in underactuated hovercraft via simulations   Order a copy of this article
    by Przemyslaw Herman 
    Abstract: The paper presents a comparison of several selected trajectory tracking controllers used for an underactuated hovercraft. The aim of the study is to check if algorithms that have proved to be effective for another class of vehicles can be adapted to control a hovercraft. In order to compare the effectiveness of the controllers, one that is exclusively designed to control the hovercraft and three others that are suitable for the control of underactuated underwater vehicles were examined. This study also proposes a methodology for simulation analysis of control algorithms. The initial simulation tests demonstrated on the 3-DOF hovercraft model show the results that can be obtained by using each control algorithm under the proposed assumptions.
    Keywords: underactuated hovercraft; nonlinear control; trajectory tracking; simulation.

  • Position tracking and balancing control of ball balancer system using intelligent controllers   Order a copy of this article
    by Ankita Varshney, Bharat Bhushan, Rupam Singh 
    Abstract: This paper develops an intelligent control approach for achieving the nonlinear control of a two degrees of freedom (2DoF) ball balancer system. The ball balancer system provides an example of an inherently unstable and underactuated electromechanical system that can be used to realise the problem of position tracking and balancing control in robotic systems. Besides, intelligent control takes into consideration the system characteristics and parameters and incorporates the heuristic knowledge and a human logical approach to best train the controller for achieving the desired control task. In this research, the robustness of the intelligent controller is realised by developing an adaptive neuro-fuzzy inference system (ANFIS), which is applied to the ball balancer system to achieve position and balancing control. The numerical simulations are carried out using the first-principles method to perform the system modelling, design, and development of the control strategy for a two-dimensional ball balancer system. The performance of the proposed controller is assessed in terms of the time domain characteristics, and a comparative study is done to demonstrate the superiority of intelligent control techniques over classical control techniques.
    Keywords: adaptive neuro-fuzzy inference system; artificial neural network controller; ball balancer system; intelligent controller.

  • Track planning of an multi-rotor unmanned aerial vehicle in a complex environment space   Order a copy of this article
    by Yue Chu, Li Ying Yang, Zhong Hua Han 
    Abstract: Aiming at the dynamic track planning problem of a multi-rotor UAV in a complex environment space, this paper proposes a high-dimensionality-reduced space environment modelling method. In this way, the complexity of the environment model will be reduced and the planning efficiency will be improved. In addition, the paper proposes an improved artificial potential field (APF) method. First, obtain overall environmental information through the A* algorithm, and optimise the global path nodes. Then, improve the potential function of the APF method, and add the attraction of the global path to the UAV, so that it can guide the UAV movement smoothly. By analysing the simulation results, it can be found that this method can make up for the shortcomings of the APF method in path guidance to a certain extent. The effective combination of the two algorithms improves the UAV's path planning ability in complex environments.
    Keywords: environment modelling; track planning; A* algorithm; APF; optimised path nodes.

  • Trajectory Tracking for Mobile Manipulator Based on Nonlinear Active Disturbance Rejection Control
    by Mhmed Algrnaodi, Maarouf Saad, Mohamad Saad, Raouf Fareh, Abdelkrim Brahmi  
    Abstract: This paper designs a nonlinear active disturbance rejection control (ADRC) to solve the trajectory tracking problem of a mobile manipulator (MM) in the presence of parameters' uncertainties, and nonlinear dynamics coupling effects of the MM system. The control scheme consists of a nonlinear extended state observer (NESO) and a nonlinear proportional derivative (PD) controller. Based on the Lagrange formulation, a dynamical model of the MM is formulated, where external disturbances and modeling uncertainties are assumed to be part of the “total disturbance” which is estimated with an observer and rejected on-line in the control law. Since the proposed controller cannot be performed unless the full transformed state vector of the system model is available, an NESO is designed to estimate the transformed state vector as well as the uncertainties. The nonlinear PD controller utilizes the state estimated by the NESO, and the effect of uncertainties is cancelled on-line by the control input. Experimental results of the MM proposed tracking controller show its validity and efficiency.
    Keywords: Active disturbance rejection control, mobile manipulator, modeling uncertainty, external disturbances, nonlinear extended state observer.

  • Real-time System Identification of an Unmanned Quadcopter System Using Fully Tuned Radial Basis Function Neural Networks
    by Mohammad Fahmi Pairan, Syariful Syafiq Shamsudin, Mohd Fauzi Yaakub, Mohd Shazlan Mohd Anwar 
    Abstract: In this paper, we present the performance analysis of a fully tuned neural network trained with the Extended Minimal Resource Allocating Network (EMRAN) algorithm for real-time identification of quadcopter. Radial basis function network (RBF) based on system identification can be utilized as an alternative technique for quadcopter modelling. The number of neurons in RBF are typically determined by trial and error approach. In order to prevent the neurons and network parameters selection dilemma, RBF with EMRAN recursive training algorithm is proposed. This automatic tuning algorithm will implement the network growing and pruning method to add or eliminate neurons in current network. The EMRAN’s performance is compared with the Minimal Resource Allocating Network (MRAN) training for 1000 input-output pair untrained attitude data. EMRAN utilizes the winner neuron strategy to reduce training time for large neuron size as much as 88 hidden neurons. The results indicate that the EMRAN algorithm produces faster mean training time around 4.16 ms compared with MRAN at 5.89 ms with a slight reduction in prediction accuracy. The proposed model can predict the attitude of quadcopter using untrained data.
    Keywords: Quadcopter, System Identification, Neural Network, Fully Tuned Neural Network, Radial Basis Function,

  • An Intelligent Online Detection Approach Based on Big Data for Mechanical Properties of Hot-rolled Strip
    by Jinxiang Chen, Ziming Fan 
    Abstract: An LightGBM prediction model based on big data is presented in order to online detect the mechanical properties of hot-rolled strip in this paper, which can achieve the greater accuracy than both the existing prediction approaches and hardware detection method for the local strips. A data set of mechanical properties of hot-rolled strip is constructed firstly by collecting a steel plants hot-rolled process control parameters,which includes 17,000 samples, and every sample contains 17 input characteristics and 3 output mechanical property parameters. Based on the data set, an LightGBM intelligent prediction model is established and trained to predict the three mechanical properties of the hot-rolled strip steels. 17,000 data of hot rolling mill are used to verify the effectiveness of the model. Results show that the prediction accuracy for tensile strength, compressive strength and elongation are 0.99971, 0.99835, and 0.99631, respectively. Especially, the prediction accuracy for elongation is higher than the existing methods.
    Keywords: Intelligent prediction; LightGBM; Hot rolled strip; Machine learning; Big data analysis; Steel mechanical properties

  • Modeling and Optimized Gait Planning of Biped Robots with Different Leg Mechanisms
    by Behnam Dadashzadeh, Akbar Allahverdizadeh, Mehdi Azhdarzadeh 
    Abstract: Biped robots with point feet demonstrate faster gaits and more natural dynamics, although planning optimal mechanisms and gaits, and designing stable control strategies for them is difficult. This research focuses on modeling and gait generation optimization of four different real biped models that include practical extended models of the theoretical SLIP and compass gait as a novelty of the work. All of the models have point feet, their torso angle is constrained, and they move in the sagittal plane. The first model is a kneed Biped model without spring which is a 5-rigid-link robot with four actuators in its hip and knees. The second model, a kneed biped model with springs in shins is very similar to the first model, but its shins have linear springs. These springs make the system underactuated and their passive vibration makes calculations and gait generation very difficult. The 3rd model is a semi-telescopic springy biped model. For this robot in the single support phase of walking, the weight-bearing springy stance leg is straight and the other leg bends its knee, swings forward, and then becomes straight and hits the ground. In the double support phase, both legs are aligned with springy telescopic joints. In this model, the existence of leg springs increases the cost of transport and gait error. For the 4th model, the semi-compass gait with kneed swing leg, in the single support phase, the knee of the stance leg stays straight, and the swing leg bends its knee to clear the ground, then it becomes straight and hits the ground. Dynamic equations of the different phases are combined to create a dynamic model of a full walking gait. In the following step, optimization parameters, objective functions and constraints are presented, and successive stages of optimization are completed to find the optimal gaits. The efficiency of the gaits and required motor torques for the optimal gait of each model are illustrated.
    Keywords: Biped robot, Walking, Modeling, Gait Optimization

  • A Novel Double-mGBDT-based Q-Learning
    by Qiming Fu, Shuai Ma, Dawei Tian, JianPing Chen, Zhen Gao, Shan Zhong 
    Abstract: This paper proposes a novel Double-mGBDT-based Q-learning algorithm. Compared with traditional deep reinforcement learning, the proposed algorithm uses the mGBDT to replace the DNN, where the mGBDT is introduced as the function approximator. In the learning process, based on the state, we use the Bellman equation to construct the target value, which is used to train the mGBDT in an online manner. Like DQN, we also adopt two mGBDT frameworks, which are used to address the problem of easy divergence. To verify performance, we apply the proposed algorithm DQN and mGBDT to the traditional benchmark problems in CartPole and MountainCar. The results show that the proposed algorithm can converge to the optimal policy, and compared with DQN, the proposed algorithm’s stability is much better after convergence.
    Keywords: deep learning; reinforcement learning; mGBDT

  • A new super-twisting sliding mode control based direct instantaneous power control of PWM-rectifier connected to grid
    by Arezki Fekik, Hakim Denoun, Mohamed Lamine Hamida , Sundarapandian Vaidyanathan, Nacera Yassa 
    Abstract: A new super-twisting sliding mode control (STSMC) based direct instantaneous power control (DPC) of PWM-recti er connected to grid is studied in this paper. The new STSMC-DPC scheme uses instantaneous power controllers. The new scheme does not use current controllers as with traditional vector control. The two regulators possess a design parameter that facilitates to adjust their behaviour between a linear operation of the PI type and a behavior in conventional sliding mode with constant gain. Our tests demonstrate that STSMC-DPC shows a robust behaviour and that it functions without chattering in steady state as in a classical regulator. The results obtained are very relevant and satisfactory for the control of the PWM converter without sensor in terms of the reduction of the chattering as well as an operation under a power factor and having a low THD of the short absorbed and uncoupled control of the instantaneous powers.
    Keywords: Direct power control; sliding mode control; super-twisting SMC; rectifier; converter; regulator; robust control; power factor; PWM; SVM; THD; UPF.

  • Back-propagation algorithm to estimate the parameters of auto-regressive exogenous model
    by Tianyang Xu, Jing Chen, Yingjiao Rong 
    Abstract: This paper proposes a back-propagation (BP) algorithm to estimate the parameters of Auto-Regressive exogenous (ARX) models. By using the SAG method, the proposed algorithm identifies the weights/parameters of the neutral network constructed for the ARX model. Furthermore, in order to decrease the oscillation phenomenon in the SAG algorithm, two modified SAG algorithms are developed. A simulation experiment is presented to verify the effectiveness of the proposed methods.
    Keywords: System identification; SAG; Sliding data window; Weighted; BP neural network

Special Issue on: SCC-2019 Recent Advances in Systems and Electrical Engineering

  • Multi-Weld defects detection based on Gabor filter and Hough Transform
    by chiraz ajmi 
    Abstract: Weld defect detection is an important application in the field of Non Destructive Testing (NDT). These defects are mainly due to manufacturing errors or welding processes. In this context, image processing especially segmentation is proposed to detect and localize efficiently different types of defects. It is a challenging task since radiographic images have deficient contrast, poor quality and uneven illumination caused by the inspection techniques. In this article, we propose a robust and automatic method based on the combination of Gabor and Hough transform to detect two major defect types from mono or multi-welds defects images. It consists of two main stages which are the preprocessing and the segmentation step. The first one is based on the Gaussian filter and contrast stretching. The segmentation step is performed using a sequence of tools starting by Gabor filter and Otsu Binarization method to isolate weld region from background and non-weld coming to Canny detector to extract edges of the spherical defect shape and finally a modified ‘Hough Transform’ technique for detection, location of linear defect and limiting the welding area. The experimental results show that our proposed method gives good performance for industrial radiographic images.
    Keywords: Weld defect; radiography; NDT; Hough Transform; Canny; Gabor filter

  • Adaptation of Deep Learning Auditory Event Recognition and Detection in Audio Surveillance Systems
    by Sara Alsubhi, Safiah Endargiri, Ahad Alkabsani, Kaouther Laabidi 
    Abstract: The work of this paper focuses on the idea of adapting computerized machines with the sophisticated abilities to relatively comprehend and act upon an auditory input of natural linguistic nature. In this paper, we emphasize the addition of acoustic-based audio inputs to the current CCTV systems for the goal of compensating any incomplete data and to reach the maximum utilization of the current surveillance systems. In this model, we apply the isolated word technique on a dataset of 8000 audio inputs dedicated to different individuals through the application of two distinct neural networks. The algorithm provides event-based detection capabilities by allowing the detection of unauthorized accesses through the automatic recognition of each spoken input together with the identity of the speaker. The proposed algorithm obtained accuracy rates of 84.1% and 80.1% for both the recognition by the speaker’s identity and the spoken input recognition. In addition, it showed its superiority over the SVM based model.
    Keywords: Classification; Automatic Speech Recognition; Natural LanguagernProcessing; Artificial Neural Network; Deep Learning; Convolutional NeuralrnNetwork; Audio Detection; Speaker Recognition; Speech Recognition; MelrnSpectrogram, CCTV.

  • Design of robust non-integer controllers for fractional order MIMO systems
    by Emna Ouhibi, Maher Ben Hariz, Faouzi Bouani 
    Abstract: The main objective of this paper is to design a robust non-integer order controller for Multi Input Multi Output (MIMO) systems. A linear parametric uncertainties fractional order model is used to describe the system dynamic behaviour. Assuming that the system can be decoupled and in order to avoid interactions between system’s inputs and outputs, the simple decoupling method has been adopted. In presence of model parameters uncertainties, the controller parameters are obtained by minimizing a min-max non-convex optimization problem. The optimized cost function is expressed using the closed loop system and the desired characteristic polynomial coefficients. So, the proposed controller ensures some closed loop temporal specifications in spite of the presence of model parameters uncertainties. Simulation examples are carried out to show the performance and the efficiency of the proposed controller.
    Keywords: robust non-integer controller, fractional order MIMO system, simple decoupler, temporal specifications.

  • The Harmful Influence of Employing a Large Number of Pilot-Resources on the Performance of Massive MIMO Systems
    by Abdelfettah BELHABIB, Mohamed BOULOUIRD, Moha M’Rabet HASSANI 
    Abstract: One of the severe constraints that limit the implementation of Massive Multi-Input Multi-Output (M-MIMO) systems is called Pilot Contamination (PC). To overcome this problem, Soft Pilot Reuse (SPR) strategy was proposed, which aims to properly allocate the Pilot Sequences (PS) to the users based on their properties e.g Quality-of-Service. Despite its flaws -that can damage the spectral efficiency-, the SPR strategy has been, heavily, employed as a decontaminating strategy. To reveal the weakness of this approach, this paper adopts a SPR based-strategy that separates the users within cells based on their large scale fading coefficients, therefore, because the edge-users (EUs) are mostly affected by the PC compared to the center-users (CUs), a set of orthogonal pilots is allocated to the EUs of the overall cells, while the CUs of each cell are obliged to reuse the same set of orthogonal pilots as the CUs of adjacent cells.
    Keywords: Massive MIMO; Pilot Contamination; Soft Pilot Reuse; Pilot Overhead; Conventional Strategy; 5G Wireless Communications.

  • A Sensorless Mixed DFIM Control Strategy based on Fuzzy-PI Speed Controller and Current Sliding Mode Controller for Electric Vehicles
    by mouna zerzeri, Adel KHEDHER 
    Abstract: This paper discusses Doubly-Fed Induction Motors (DFIM) integration possibilities in Electric Vehicle (EV) propulsion systems. The motivation behind this work is to develop an appropriate control law for DFIM to be suitable for EV applications. From this point of view, the main contributions of this study are: (i) a mixed control approach of an electric vehicle propulsion system based on a DFIM which is composed of a Fuzzy-PI controller for the mechanical mode and a sliding mode controller for the electrical one, (ii) an active power distribution law of both stator and rotor circuits connected to space vector pulse width modulation voltage source inverter, (iii) a new method to estimate speed by associating an MRAS estimator with an extended Luenberger observer in order to ensure the sensorless command and to compensate the load torque impacts. The effectiveness of the developed sensorless mixed control algorithm is proved by the obtained simulation results for different DFIM operating ranges.
    Keywords: Electric vehicle propulsion system; DFIM; Fuzzy-PI controller; sliding mode controller; power distribution; MRAS; Luenberger observer

  • Stability Analysis and Fault-Tolerant Control of neutral systems
    by Rabeb Benjemaa, Aicha Hsoumi, Saloua Bel Hadj Ali Naoui 
    Abstract: This work studies the problem of stability analysis and fault-tolerant control of neutral systems. Improved stability criteria is obtained by applying Lyapunov method and Linear Matrix Inequality (LMI) technique. An adaptive-observer is designed to detect and estimate fault, and a new control law is proposed to achieve fault compensation. A numerical example is given to illustrate our theoretical results.
    Keywords: Neutral time-delay system, Stability, Fault detection, Fault estimation, Fault Tolerant Control (FTC), Adaptive observer, Linear Matrix Inequality (LMI).

  • Open-Switch Fault Detection Scheme in Wind Energy Conversion System Based on Rotor Currents Analysis
    by Bilel Touaiti, Hechmi Ben Azza, Mohamed Jemli 
    Abstract: To deal with the performance and service continuity of Doubly Fed Induction Generator (DFIG) based wind energy conversion systems during open-switch Insulated Gate Bipolar Transistor (IGBT) fault, a fault-tolerant Voltage Source Inverter (VSI) is proposed. The fault-tolerant VSI is designed with redundancy leg to replace the faulty leg after open-switch fault occurrence. In this investigation, we propose a new topology of DC-Bus tied DFIG based on uncontrolled rectifier in stator side. A Field Oriented Control (FOC) scheme is used in this paper to control the DFIG. The open-switch IGBT fault is studied and a fault detection scheme based on rotor currents analyzing within healthy and faulty conditions is proposed. Case study results show that the proposed fault-tolerant VSI can ensure the service continuity of DFIG-DC system. Experimental results are presented in this paper to validate the proposed fault detection scheme.
    Keywords: Doubly Fed Induction Generator (DFIG); Fault Tolerant Voltage Source Inverter (VSI); Redundant leg; DC-Bus.

Special Issue on: Modelling and Simulation Techniques for Industry Applications

  • Identification of MISO Wiener systems using the LMI algorithm
    by Lincheng Zhou, Xiangli Li 
    Abstract: This paper focuses on a new identification method for multiple-input single-output (MISO) Wiener nonlinear systems, in which the static nonlinear block is assumed to be a polynomial. The basic idea is to establish a MISO Wiener nonlinear identification model with polynomial nonlinearities by means of the key term separation principle. Then, a new identification method based on Levenberg-Marquardt iterative (LMI) search techniques, which can make full use of all the measured input and output data, but also automatically change the search step-size according to the change values of the quadratic criterion function, is derived to obtain an accurate and fast parameter estimation of the model. Finally, the simulation results demonstrate the efficacy of this method.
    Keywords: LMI search; Parameter estimation; Iterative algorithm; Multiple-input single-output system; Wiener nonlinear system.

  • Hybrid projective synchronization of fractional-order network system
    by lingzhong zhang, Xiangli Li 
    Abstract: The hybrid projective synchronization(HPS) of memristor-based fractional order delayed neural networks system (MFDNNs) is considered. By using the definitions and properties of differential inclusions and set-valued map, fractional order correlation inequalities are established. The hybrid projective synchronization of MFDNNs is investigated by designing feedback controller and several criteria are derived under the frame of Razumikhin-type stability theorem and Lyapunov function method. A numerical example is given to verify the conclusion.
    Keywords: Hybrid projective; Networks; Delay; Synchronization; Memristor.

  • Synchronization of inertial reaction-diffusion complex networks with mixed time delays via spatiotemporal sampling control
    by TianE Chen, ZaiHe Cheng 
    Abstract: This paper addresses the global synchronization problem of a class of inertial complex networks with reaction-diffusion terms and mixed time-varying delays. First, the spatiotemporal sampling control scheme using incomplete measurements is proposed to ensure the synchronization of the delayed inertial reaction-diffusion complex networks, which deduce the update rate of the synchronization controller. Secondly, by taking new appropriate Lyapunov–Krasovskii function, using improved Wirtinger Jensen inequalities, new synchronization criteria are derived which depend on the relationship among the sampling time interval, the feedback control gain and the sampling space interval. Finally, two numerical simulation results substantiate the effectiveness of the theoretical results.
    Keywords: reaction-diffusion, inertial complex networks, incomplete spatial measurements, spatiotemporal sampling control

  • Parameter and Time Delays Estimation Based on Compressed Sensing for MISO CARMA System Modeling
    by Taiyang Tao, Qingxi Xu 
    Abstract: This paper considers estimating parameters and time-delay for multiple input single output(MISO) controlled auto-regressive moving average(CARMA) models with unknown time delays. Inspired by compressed sensing method and hierarchical idea,rnan orthogonal matching pursuit algorithm based iterative is presented for MISO CARMA system in this paper.rnThe presented algorithm can estimate time-delay and parameters of MISO CARMA system with limited sampled data.rnAn example is given to show the effectiveness of the algorithm in this paper with a few sampled data.
    Keywords: parameter estimation; time-delay; MISO CARMA system; hierarchical idea; orthogonal matching pursuit

Special Issue on: Recent Trends of Adaptive Control and its Applications for Unmanned Systems

  • Controlling of lower order dead system by implementing using adaptive RST algorithm
    by YANZHU GUO 
    Abstract: Since the advent of time, mankind has made numerous technological advancement. Every system build is indeed time varying in nature as well as non-linear, they intend to vary with time. Dead or slow system tends to vary at a slow rate, hence controlling them is more challenging as compared to other no-linear systems. In order to control such system, we implemented an RST based control algorithm which can track the output response of the unknown system and control it with minimal error. (?) is a quantity measured in time and it is a time varying parameter for the lower order system, this is the parameter that will change with time and in turn change an entire system response. Since the system is time varying, it is bound to change its coefficients at certain point in time, which changes the system, hence the previously applied control parameters might not be suitable to control the system. Least Square (LS) algorithm is used to track the changes occurring in the system with time and thus changing the control parameter to complement the changes occurred in the system. The proposed algorithm of RST control design of slow time varying system is compiled and simulated in MATLAB environment. The proposed method is compared with the conventional PID controller and it tracks the signal faster with the same amount of work force. It provides better performance and it is more robust and effective than the traditional PID controller.
    Keywords: RST Control Algorithm, Slow Time Varying System, Dead Systems, Least Square Algorithm, Adaptive control, self-tuning Regulator.