International Journal of Modelling, Identification and Control (77 papers in press)
Observer-based output feedback integral terminal sliding mode control for nonlinear systems: multi-model approach
by Kaïs Hfaïedh, Karim Dahech, Tarak Damak
Abstract: In this paper we propose an observer-based output feedback integral terminal sliding mode control for nonlinear systems. The state estimation problem is treated by using the Utkin observer under a multi-model structure. The design of the control law is based on the sliding mode theory. In fact, we propose two types of integral terminal sliding mode, which are sign integral and fraction integral. The objective of such observer-based control algorithms is to estimate the states of the system and to stabilise the output tracking error to zero. The stability proof is demonstrated by the Lyapunov approach. A numerical example of denitrification process is presented in order to validate the performances of the proposed control laws.
Keywords: nonlinear systems; multi-model approach; integral terminal sliding mode control; state observer; output feedback control.
Active and reactive power control of a dual stator induction generator for wind energy conversion
by Fatma Lounas
Abstract: This paper deals with the active and reactive power control of a Dual Stator Induction Generator (DSIG) based Wind Energy Conversion System (WECS). The DSIG is used instead of a Doubly Fed Induction Generator (DFIG) to avoid the main drawback of the slip-ring system. The DSIG has two three-phase windings in the stator; one is used as a Power Winding (PW) and the other as a Control Winding (CW). The aim of this article is to establish the relationships between the powers delivered from the power winding and the voltages applied at the control winding terminals, to build a simplified diagram of the DSIG which permits to synthesise easily PI regulators. The DSIG-based WECS is modelled and implemented under the Matlab-Simulink environment and a set of simulation tests for both hypo-synchronous and hyper-synchronous operating modes are performed to prove the feasibility and the validity of the developed control laws.
Keywords: wind energy; MPPT; dual stator induction machine; doubly fed induction machine active power; reactive power; direct control; field oriented control; PI controller.
A hydraulic system based on the servo valve with dual input of machine and electricity
by Hao Yan, Bowen Jiang, Zheqing Zuo
Abstract: The hydraulic system based on the servo valve with dual input of machine and electricity consists of the valve control system and the mechanical feedback device, which has a higher reliability. When the power of the system is cut off, the system can continue working until the actuator returns to the original position. This system is widely used in some occasions with higher reliability requirements. In this paper, the mathematical model of the system is established, where a certain transmission ratio between the actuator and the mechanical feedback is considered. Meanwhile, the key system parameters are analysed in order to reflect their influences on the system performance. It is obtained that the uncertainties of key parameters of the hydraulic amplifier have a certain impact on the dynamic and static characteristics of the system.
Keywords: servo valve; dual input; mechanical feedback; dynamic and static characteristics.
A divide-and-conquer based improved genetic algorithm for network selection in a heterogeneous wireless network
by Hui Sun, Chuang Yang, Rui Wang, Sabir Ghauri
Abstract: Developing and using wireless networks is a trend to serve passengers in aircraft cabins. Cognitive radio technology can be used in the aircraft cabin wireless environment to solve the spectrum resource scarcity problem. Heterogeneous network access issue should be noticeable in cognitive radio wireless networks. In this paper, a improved genetic algorithm (GA) based on the divide-and-conquer is proposed to handle this problem. The proposed approach is compared with original GA, Particle Swarm Optimisation (PSO) algorithm and Tabu Search (TS) algorithm. The simulation results prove that the proposed method is valid.
Keywords: aircraft cabin; wireless network; heterogeneous; divide-and-conquer.
Modelling and multi-loop selective control of industrial coal pulveriser
by Vini Dadiala, Jignesh Patel, Jayesh Barve
Abstract: Coal-based power generation continues to be the key player in power generation. However, the efficiency of a thermal plant lies in the range of 30-40%, a sizably less value. Pulverisation of coal is an important but an energy-intensive process. Efficient control of the pulveriser can improve the efficiency of the overall plant. This paper discusses various computational results and their analysis for the case study of a coal pulveriser carried out at a thermal power plant in Gujarat, India. It proposes a more accurate mathematical model for a pulveriser with a static classifier and a 3PI (Proportional Integral) with selective control for improved performance. The proposed model is validated with real plant data from the 150 MW ESSAR thermal power plant, Gujarat. It is observed that the proposed model captures the system dynamics more effectively than the models existing in the literature. A 3PI with selective control strategy is proposed where the primary air flow is selected from the mill differential pressure loop and air-fuel ratio loop depending on operating conditions. It is observed that the new model with proposed control has better load disturbance rejection properties and is found to be more robust to parametric variations compared with the control strategy employed in the industry, wherein the mill differential pressure is controlled manually.
Keywords: coal pulveriser; static classifier; coal mill modelling; parametric analysis; 3PI with selective control.
XGBoost-PCA-BPNN prediction model and its application on predicting the effectiveness of non-surgical periodontal treatment
by Jinxiang Chen, Dong Shi, Jinqi Fan, Huanxin Meng, Jian Jiao, Ruifang Lu
Abstract: An XGBoost-PCA-BPNN predication model is presented to classify and predict the objects based on the big data set with uncertain and coupling multi-dimensional characteristics, because the existing anyone single machine learning model cannot obtain the high prediction performances when it is applied to deal with the above problem. The XGBoost-PCA-BPNN model is applied to predict the effectiveness of non-surgical periodontal therapy (NSPT) for Chinese population with chronic periodontitis and the high prediction accuracy is obtained in this paper. Firstly, the advantages and the disadvantages of the existing machine learning approaches are analyzed. The XGBoost can handle\r\neffectively the coupling problems among multi-dimensional characteristics in big data sets. The PCA can reduce the dimension of inputs. BPNN can improve the accuracy of calculation, but the overfitting problems would be happened when it is used to handle the objects with multi-dimensional characteristics. The XGBoost-PCA-BPNN predication model is presented by combining XGBoost, PCA with BPNN in order to predict the objects with uncertain and coupling multi-dimensional characteristics. The model is verified by applying it to predict the effectiveness of NSTP for the big data set with 45,000 clinical chronic periodontitis sites. 30,000 sites are used as training samples and 15,000 sites are regard as testing data. Prediction results show that the Xgboost-PCA-BPNN model has higher predication accuracy, faster convergence speed and better stability than Logistic regression, Xgboost, Xgboost-Logistic regression. The $R^2$-score of the Xgboost-PCA-BPNN model is 0.943. In addition, it can be seen that the effectiveness of NSTP are mainly influenced by PD, BI, sites,age.
Keywords: classification prediction; XGBoost; BPNN; non-surgical periodontal treatment; big data analysis; chronic periodontitis; effectiveness.
Decoding fNIRS-based imagined movements associated with speed and force for a brain-computer interface
by Xinglong Geng, Zehan Li
Abstract: Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive technology applied in brain-computer interface (BCI) systems. This study investigates fNIRS-based imagined hand-clenching tasks, indicating that the combinations of speed and force have distinct patterns that can be decoded to develop a BCI system. Twelve healthy participants were instructed to perform imagined left or right hand-clenching tasks; oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) concentrations were acquired from motor cortex using a multi-channel fNIRS system. A feature selection method based on mutual information was employed to select the optimal features for classification, and support vector machine (SVM) was used as a classifier, resulting in average accuracies of 84.9% and 86.1% for classifying left and right imagined movements, respectively. Compared with traditional fNIRS-BCI system, this study provides a possibility to generate a new control pattern for brain-controlled robots, e.g. speed or force control. There is also a potential application to combine fNIRS-BCI system with the exoskeleton to produce a complex rehabilitation strategy.
Keywords: brain-computer interface; hand clenching; support vector machine.
Linear discrete-time modelling and hybrid fault-tolerant controller design for complex systems with component and sensor faults
by Chunxiao He, Xisheng Li
Abstract: A linear discrete-time model with the additive fault is constructed for the systems with component faults and sensor faults. A hybrid controller including the state feedback controller, the $H_\\infty$ filter and the fault-tolerant controller with $H_\\infty$ performance $\\gamma$ is designed in this paper. By using the Lyapunov function and linear matrix inequalities (LMI) approach, the theorem solving the designed controller gains is derived. The effectiveness of the presented approaches is verified by using them to control the Van der Pol circuit system with the ageing fault of components. Simulation results show that the designed controller can suppress the influence caused by components and sensor faults and stabilise the systems under meeting $H_\\infty$ index.
Keywords: fault-tolerant controller; modelling; hybrid controller; $H_\\infty$ filter; additive faults; sensor faults; components.
A survey of control strategies for grid connected wind energy conversion system based permanent magnet synchronous generator and fed by multi-level converters
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.
Input-to-state stability of systems with non-instantaneous impulses
by Cheng Liu, Zheng Fang, Jing Chen
Abstract: In this paper, we investigate the input-to-state stability of systems with non-instantaneous impulses. By using the Lyapunov function with indefinite derivative and the average dwell time condition, we get a sufficient condition for the input-to-state stability of systems with non-instantaneous impulses, then we give an example in the end to show the efficiency of the theoretic result obtained in this paper.
Keywords: impulsive systems; non-instantaneous impulses; input-to-state stability; average dwell time condition.
Global stability and optimal control of melioidosis transmission model with hygiene care and treatment
by Ratchada Viriyapong, Sunisa Tavaen
Abstract: A compartmental deterministic mathematical model for melioidosis transmission is proposed. It involves human and animal population and bacteria. We present two main equilibrium points (disease-free and endemic) with the analysis of their local stability. The basic reproduction number and its sensitivity index to the parameters in the model are calculated. Lyapunovs direct method is used to analyze the global stability of endemic equilibrium point. Further, by using Pontryagin's minimum principle, the optimal control problem is constructed with two controls, i.e. hygiene care and treatment controls for human population. Finally, the numerical simulations are established and our results show that a combination of the two controls gives more impact in reducing the numbers of infected human and bacteria than in reducing the number of infected animals. Because melioidosis prevalence is still increasing, more effort in sharing knowledge and controlling the spreading of this disease is still much required.
Keywords: melioidosis; hygiene care; optimal control; Lyapunov’s direct method; Pontryagin's minimum principle.
Nonlinear controller for MPPT based photovoltaic system under variable atmospheric conditions
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.
A coevolutionary quantum krill herd algorithm for solving multi-objective optimization problems
by Zhe Liu, Shurong Li
Abstract: Multi-objective optimisation (MOO) has always been a challenging problem that received considerable attention in practical engineering applications owing to the multicriteria objectives. This paper presents a coevolutionary quantum krill herd algorithm (CQKH) as a novel numerical method for solving MOO. The CQKH is a quantum-inspired evolutionary algorithm that improves the krill herd algorithm (KH) based on quantum representation and quantum rotation gate. As a result, CQKH has a stronger robustness and the capability of finding the optimal or near-optimal solution faster by fewer individuals. In addition, the CQKH adopts a coevolutionary technique named multiple populations for multiple objectives (MPMO) to obtain the whole Pareto optimal front. The computation results of CQKH on numerical tests with various characteristics demonstrate its effectiveness and superiority compared with some state-of-the-art algorithms.
Keywords: multi-objective optimisation; coevolutionary quantum krill herd algorithm; multiple populations for multiple objectives; quantum representation; quantum rotation gate.
Modelling, identification, implementation and MATLAB simulations of multi-input multi-output proportional integral-plus control strategies for a centrifugal chiller system
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.
Coordination control and obstacle avoidance for a team of mobile robots in an unknown environment
by Mohammad Habibur Rahman, Sucheta Roy, M.D. AssadUz-Zaman
Abstract: This paper presents a dual-level control structure for controlling a mobile robot and/or a team of mobile robots to navigate through an unknown (static or dynamic) environment. The higher-level controller operates in cooperation with robots state estimation and mapping algorithm, Extended Kalman Filter Simultaneous Localization and Mapping (EKF-SLAM), and the lower-level controller controls the motion of the robot when it encounters an obstacle, i.e., it reorients the robot to a predefined rebound angle and move it straight to maneuver around the obstacle until the robot is out of the obstacle range. The higher-level controller jumps in as soon as the robot is out of the obstacle range and moves the robot to the target destination. The obstacle avoidance technique involves a novel approach to calculate the rebound angle. Simulation results verified the effectiveness of the proposed control law. Further, a pilot experiment was carried out to validate the simulated results. The experimental results show that the proposed dual-level control structure can be effectively used to maneuver a mobile robot or a team of mobile robots to navigate through a dynamic environment.
Keywords: EKF-SLAM; mobile robots; dual-level motion controller; obstacle avoidance.
Population dispersal and optimal control of an SEIR epidemic model
by Soovoojeet Jana, Manotosh Mandal, Tapan Kumar Kar
Abstract: This paper formulates and analyses an SEIR-type epidemic model with the effect of transport-related infection between two cities in the presence of treatment control.
The dispersal of populations from one city to another city has an important impact on the dynamics of disease evolution. The proposed model system is studied in three different cases: (i) no population dispersal, (ii) dispersal for susceptible and exposed individuals only, and (iii) dispersal for all classes of the population. The most important parameter in an epidemic model is the basic reproduction number which is directly connected to the severity of the disease. It is calculated for all the different cases of the model system. It is found out that the equilibrium is disease-free if the basic reproduction is less than unity, otherwise the disease may remain in the system. In addition, the optimal control problem is constructed and solved analytically and numerically by considering the treatment control as a control variable. Further, we present a numerical simulation to confirm the analytical results. Finally, we show a comparison of the result of our predicted model with the real data of SARS (severe acute respiratory syndrome) outbreak in 2003 in Hongkong.
Keywords: infectious disease; transport-related infection; basic reproduction number; optimal control.
An improved ELECTRE-III method for recommending new energy vehicles with heterogeneous decision-making information
by Meng Fanyong, Ding Yuqing
Abstract: New energy vehicle (NEV) is the development direction of automobile industry supported by the Chinese government. Different brands of NEVs have different performance, and it is not an easy thing to select the suitable NEVs. This paper first analyses the evaluation factors and establishes the index system. Then, a method for heterogeneous information transformation is introduced, and a method for determining the criteria weights based on linguistic variables is provided. After that, an improved ELECTRE-III method for recommending NEVs is proposed that can address the situations where there are heterogeneous decision-making information and unknown weighting information. To illustrate the practicality of the new method, a case study is provided. Meanwhile, comparison analysis with two existing methods is made.
Keywords: multi-criteria decision making; new energy vehicle; ELECTRE-III method; heterogeneous information.
Multiple U-model control of uncertain discrete-time nonlinear systems
by Weicun Zhang, Zhaolong Zhang, Qing Li, Zhuoer Xue
Abstract: Based on U-model concept and multiple model methodology, this paper presents a weighted multiple U-model control scheme to address the control problem of some classes of discrete-time nonlinear systems with large parameter uncertainties including parameter jumps, which is a difficult problem without unified solution up to now. Simulation results on two types of nonlinear system with large parameter uncertainties verified the effectiveness of the proposed scheme.
Keywords: U-model control; multiple model control; nonlinear system.
Kinematic modelling and simulation of PID controlled SCARA robot with multiple tool end effectors
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
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
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
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
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
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
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
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
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
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
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
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
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
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;
A new multistable hyperjerk dynamical system with self-excited chaotic attractor, its complete synchronisation via backstepping control, circuit simulation and FPGA implementation
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
by Yi Han
Abstract: —With the low price of natural gas, and its low emissions, signi?cant 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 controloriented turbocharged pre-mixed lean burn natural gas engine mean value model (MVM). This model is designated for natural gas engine controller design, control algorithm development, and ?rst step validation. The model is implemented in the MATLABr Simulinkr environment. The model is validated with a 10L natural gas engine for power generation applications.
Keywords: Modeling; Control systems; Natural gas; Internal combustion enginesrn
Displacement Velocity Control of a Mechanised Welding System by Low-Cost State Feedback Controller
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 the industry, the use of robots and mechanised systems in this process is widely used. As a result, researches about autonomous and semi-autonomous welding systems comes an important rule to reduce losses and improve welding quality. In this bias, 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
by mehdi rakhtala
Abstract: Polymer electrolyte membrane fuel cell (PEMFC) is an appropriate candidate in renewable energy resources to using in vehicular, industry and other applications. This research paper concentrates on the nonlinear model of PEMFC system. The load fluctuations in fuel cell stack affect the life time and causes fuel cell stack damaging and aging. So, closed-loop control system is suggested to regulate of oxygen excess ratio (?o_2) in desired value. In this paper, a self-tuning fuzzy logic PID (FPID) controller is suggested for a PEMFC air supply system because the fuel cell is very severe nonlinear system. The oxygen excess ratio is regulated to a desired value by adjusting of air ?ow rate. The control scope is to adjust the oxygen excess ratio in its operating range by controlling of compressor. Proposed FPID controller is a nonlinear and robust controller that assure good efficiency around each equilibrium point under model uncertainties and avoid 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
by Falu Weng, Huan Wang, Yuanchun Ding
Abstract: This paper investigates the robust energy-to-peak stability analysis and controller design for 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 include 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 be energy-to-peak stability and stabilization. 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
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 minimizing 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
Modeling and experimental study on hierarchical throttling water distributor
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 summarize the change rules therein. Finally, according to the experimental results, suggestions for effective evaluation and parameter optimization are proposed. The research results can play a good guiding role in the design of large-pressure differential hierarchical throttling water distributor.
Keywords: Water Distributor; Flow Field; Experimental Research; Optimization
Image semantic segmentation based on improved DeepLab V3 model
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
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 represent a mobility device applied temporarily during the rehabilitation process or permanently as an assistive device. As a permanent device, they have a deep impact on the body due to the reactive force redistributed on the upper limbs. We present a review on the development and implementation of an innovative cushioning crutch-mounting device as well as a sensorial system for gathering feedback data. Following, we propose a Bond Graph mathematical model to compare the traditional Lofstrand Crutches (LC) with modified LC (mLC). 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 minimizations on the upper limbs force redistribution, avoiding further movement disabilities for permanent users.
Keywords: Lofstrand Crutches; Adapted Lofstrand Crutches; Bond Graph Modelling; BG Model; Modelling; Control; 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
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-jumping out of the sheave groove. The 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 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 was proposed to reduce the spatial transverse vibrations of a catenary, numerical simulation validated the feasibility. The paper will provide good technical supports 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 Bidirectional Active Balancing Model for Lithium-ion Battery Pack
by Qiuting Wang, Wei Qi
Abstract: The performance of single cell and serial/parallel pack of lithium-ion battery will be inconsistent, in case of the deviation of production process and the difference of application environment. It will easily lead to the decline of the overall capacity of 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 equalization cycle. The 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 strategy such as low energy transfer efficiency, long equalization time and unsuitable for large capacity battery pack. 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
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 analyzed. 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
by Aritro Dey
Abstract: A new filtering algorithm has been 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 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 has been demonstrated in simulation over its non-adaptive counterpart and the competing algorithms of adaptive nonlinear filters with the help of some nontrivial case studies. Additionally, suitability of the proposed algorithm is also 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 3-Mass Models for Electromechanical Motion Systems
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 optimization; transfer function type; poles and zeros; frequency domain; frequency response function; FRF.
Several structure pool based identification algorithms for ARX models: Order and parameter estimation
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 which 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 applied for systems with unknown orders and parameters, thus are more promising in engineering practice. The simulation example is utilized 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
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 utilizing the partial-to-total output of the AFC signal was investigated. The hybrid PID-AFC-GA controller gives superior disturbance rejection efficacy than the other proposed methods.
Keywords: Quadrotor control, Newton-Euler method, Active force control, PID controller, Genetic algorithm optimization, Disturbance rejection, Trajectory tracking.
Frequency Characteristics of A Phase Optimized Active Disturbance Rejection Control
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 optimization law (POL), which is of simple structure and easy to be realized, is proposed. Based on the POL, both a phase optimized extended state observer (POESO) and a phase optimized 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 has been analyzed 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. 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 analyzed 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; Optimized Phase
Modeling and structure optimization on throttle tube of pre-throttle water distributor
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 analyzed, and the test results are drawn. according to the test results, the optimal pipe diameter and circle number selected under different pressure drop are determined. The research results can play a good guiding role in the design of pre-throttle water distributor.
Keywords: water distributor;Modeling;throttle tube;pressure drop;flow rate.
Special Issue on: ICMIC 2019 Mathematical Modelling and Advanced Control Approaches of Nonlinear Complex Dynamics
Development of human lower extremity kinematic and dynamic models for exoskeleton robot-based physical therapy
by S.K. Hasan
Abstract: The World Health Organization reports that approximately one billion people are disabled in the world. Rehabilitation programs help promote functional recovery in disabled individuals. Exoskeleton robot-based physical therapy is an appealing solution for a large number of disabled people. Mechanical design, modelling, and control of exoskeleton robots require anthropometric data. A majority of anthropometrical data is not readily available from a single source. Furthermore, seven degrees of freedom human lower extremity kinematic and dynamic models are also not available. This paper presents dynamic modeling and simulation of the human lower extremity. The Lagrange energy method is used for developing a lower extremity dynamic model. The dynamic simulation utilizes a Computed torque controller. A Sliding mode controller is also developed for practical applications. The Sliding mode controller is a robust control scheme, which works efficiently in the presence of disturbances and parameter variations. Human lower extremity degrees of freedom, range of motion of various joints are integrated into the proposed model. Simulation results show the performance of the controller, joint torque, and power requirements for tracking a specified trajectory. The proposed model can be used as a reference to develop and verify a human lower extremity dynamic model. Since the human lower extremity exoskeleton robot should possess a similar dynamical behavior, the proposed model can easily produce the dynamic model of lower extremity exoskeleton robot by considering the masses, inertial properties and joint frictional forces of links in the exoskeleton robot. Because of its performance in the presence of simulated disturbances and parameter variations, it is seen that the sliding mode controller is an effective choice for controlling a real robot.
Keywords: physiotherapy; exoskeleton robot; lower extremity anthropometric parameters; sliding mode controller; lower extremity kinematic and dynamic model.
Identification of a deterministic Wiener system based on input least squares algorithm and direct residual method
by Shaoxue Jing
Abstract: The Wiener system is a type of block-oriented system that consists of a linear model followed in series with a static nonlinear element. In this work, two novel identification methods are proposed to estimate the order and parameters of a class of Wiener system whose linear part is a finite impulse response function and whose nonlinear inverse function is a polynomial. First, a direct order identification method using the input-output data rather than an unknown intermediate variable is designed to estimate the order of the linear part. The method decreases the computational cost and improves the accuracy of order estimation, because it doesn't require calculating the intermediate variable. Second, an identification algorithm minimising the input prediction error is developed to obtain parameters of the Wiener system. Third, a numerical simulation and a case study verify the proposed algorithm. The proposed methods, with a little modification, can be applied to identify other block-oriented systems.
Keywords: order estimation; parameter estimation; Wiener system; residual analysis.
Robust pole-placer power system stabilisers design via complex Kharitonovs theorem
by Mohamed Ayman, Mahmoud Soilman
Abstract: In this paper, synthesising robust three-parameters power system stabilisers (PSSs) having a common form of? (x?_1+x_2 s)/(1+x_3 s) is presented. Graphical characterisation of the set of stabilising PSSs is carried out using D-decomposition whereas the controller-parameter space is subdivided into root-invariant regions. The dynamic model of single-machine infinite-bus system (SMIB) is considered to accomplish the design. Rather than Hurwitz stability, D-decomposition is extended to consider D-stability, where D refers to a pre-specified damping cone in the open left half of the complex plane to enhance time-domain specifications. Pole clustering in the damping cone is inferred by enforcing Hurwitz stability of a complex polynomial accounting for the geometry of such a cone. Parametric uncertainties of the model imposed by continuous variation in load patterns is captured by an interval polynomial. As a result, computing the set of all robust D-stabilising PSSs calls for Hurwitz stability of a complex interval polynomial. The latter is tackled by a complex version of Kharitonovs theorem. A less-conservative and computationally effective approach based on only two extreme plants is concluded from the geometry of the stability region in the controller parameter plane. Simulation results affirm the robust stability and performance of the proposed PSSs over wide range of operating points.
Keywords: PSS design; robust control; D-decomposition; interval polynomial; Kharitonov’s theorem; complex polynomials.
Model-predictive-control complex-path tracking for self-driving cars
by Wael Farag
Abstract: In this paper, a comprehensive Model-Predictive-Control (MPC) controller that enables effective complex track manoeuvring for Self-Driving Cars (SDC) is proposed. The paper presents the full design details and the implementation stages of the proposed SDC-MPC. The controller receives several input signals, such as an accurate car position measurement from the localisation module of the SDC measured in global map coordinates, the instantaneous vehicle speed, and the reference trajectory from the path planner of the SDC. Then, the SDC-MPC generates a steering (angle) command to the SDC in addition to a throttle (speed/brake) command. The proposed cost function of the SDC-MPC (which is one of the main contributions of this paper) is very comprehensive and is composed of several terms. Each term has its own sub-objective that contributes to the overall optimization problem. The main goal is to find a solution that can satisfy the purposes of these terms according to their weights (contribution) in the combined objective (cost) function. Extensive simulation studies in complex tracks with many sharp turns have been carried out to evaluate the performance of the proposed controller at different speeds. The analysis shows that the proposed controller with its tuning technique outperforms the other classical ones like PID. The usefulness and the shortcomings of the proposed controller are also discussed in detail.
Keywords: MPC control; self-driving car; autonomous driving; MPC tuning.