International Journal of Modelling, Identification and Control (70 papers in press)
Designing Route Guidance Strategy with Travellers Stochastic Compliance: A Bi-level Optimal Control Procedure
by Wei-li Sun, Ling-long Hu, Ping Li, Hui Wang
Adaptive neural networks for AC voltage sensorless control of three-phase PWM rectifiers
by Adel Rahoui, Hamid Sediki, Ali Bechouche, Djaffar Ould Abdeslam
Abstract: In this paper, a new adaptive grid voltages estimator for AC voltage sensorless control of three-phase pulse-width modulation (PWM) rectifier is proposed. The proposed method is based on a simple adaptive neural network (ANN) to estimate online the grid voltages. The main advantage of this method is its simplicity and it requires low computational cost. The ANN estimator is inserted in voltage-oriented control (VOC) to perform an AC voltage sensorless control scheme. During the startup process, the proposed ANN estimator is also used for estimating initial values of the grid voltages. For accurate estimation, adaptive neural filters (ANFs)-based pre-filtering stage of the input voltages and AC-line currents is added. Experimental tests are carried out to verify the feasibility and robustness of the proposed ANN estimator. Experimental results show good performances of the proposed AC voltage sensorless control scheme in normal and severe grid voltage conditions.
Keywords: adaptive neural network; adaptive neural filter; pulse-width modulation rectifier; diode rectifier; grid voltages estimation; voltage-oriented control; sensorless control; startup process; experimental verification; stability.
Complete Synchronization of Supply Chain System Using Adaptive Integral Sliding Mode Control Method
by Hamed Tirandaz
Abstract: In this paper, synchronization problem of supply chain chaotic system is carried out with active and adaptive integral sliding mode controlling method. Active integral sliding mode synchronization is performed for two identical supply chain systems by assuming that all parameters of the systems are known. When the internal and external distortion parameters of the system are considered unknown, an appropriate feedback controller is developed based on the adaptive integral sliding mode control mechanismrnto synchronize two identical supply chain chaotic systems and to estimate the unknown parameters of the systems. The stability evaluation of the synchronization methods are performed by the Lyapunov stability theorem. In addition, the performance evaluation of the designed controllers and the theoretical analysis are verified by some illustrative numerical simulations. Simulation results indicate excellent convergence from both speed and accuracy points of view.
Keywords: Supply chain system, Integral sliding mode control, Active control, Adaptive control
Self-adaptative multi-kernel algorithm for switched linear systems identification
by Lamaa Sellami
Abstract: This paper deals with the identification problem of switched linear systems based on a measurement dataset. The great challenge of this problem lies in the dataset available for identification. Indeed, this set is a mixture of observations generated by a finite set of different linear submodels that interchange between each other with an unknown and unavailable switching dynamics. To overcome this problem, we developed an identification approach that consists of determining simultaneously a linear regression function that models each submodel and a switching signal estimation via a self-adaptive clustering algorithm. The regression function is identified based on the multi-kernel Support Regression Vector (SVR) approach. This identification approach consists of decomposing the regression vector into several blocks and assigning a kernel function to each block. However, the switching signal estimate is provided by an unsupervised classification algorithm with self-adaptive capacities. According to a similarity measure, this identification process is achieved through three main stages: classes creation (with an initialisation procedure), online classes adaptation and classes fusion. To evaluate the performance of the proposed method we include some simulation results.
Keywords: switched linear systems; system identification; multi-kernel support regression; machine learning.
D-stability of parameter-dependent linear systems including discretization by Taylor series expansion and search in a scalar parameter.
by Marco Aurelio Leandro, karl Kienitz
Abstract: This work addresses the allocation of the closed-loop poles of a discretized system from a continuous-time one with varying parameters, aiming at its control through a computer. It proposes a sufficient condition for an allocating state feedback with parameter-dependent gain. The condition is veried through a feasibility test of a set of Linear Matrix Inequalities (LMIs), based on the existence of a homogeneous polynomially parameter-dependent Lyapunov function of arbitrary degree. The main contribution of this work is the guarantee of the continuous-time system's stability and simultaneously the allocation of the closed-loop poles of the discretized system in a D-stable region. In order to allow this, the discretized model is formed by homogeneous polynomial matrices of arbitrary degree, augmented by an additive norm-bounded term, which represents the discretization residual error. Numerical examples show a larger number of feasible cases associated to the proposed condition in comparison with the condition based on a parameter-independent gain.
Keywords: Robust control; D-stability; discrete-time linear systems; parameter-dependent state feedback; linear matrix inequalities.
A novel four-dimensional conservative chaotic system without linear term, its analysis and adaptive control via integral sliding mode control
by Sundarapandian Vaidyanathan
Abstract: In this work, a novel conservative four-dimensional chaotic system without
linear term is proposed. The fundamental qualitative properties of the novel chaotic system are described with details of volume-preserving property, equilibrium points, symmetry, Lyapunov exponents and Kaplan-Yorke dimension. We show that the novel four-dimensional chaotic system has two planes and one line of equilibrium points. Next, an adaptive integral sliding mode controller is designed to stabilise the novel chaotic system with an unknown system parameter. Moreover, an adaptive integral sliding mode controller is designed to achieve global chaos synchronisation of the identical novel chaotic systems with an unknown system parameter. The adaptive control mechanism helps the control design by estimating the unknown parameter. Numerical simulations using MATLAB are shown to illustrate all the main results derived in this work.
Keywords: chaos; chaotic systems; novel system; adaptive control; sliding mode control; chaos synchronisation.
Feedback control of bilinear distributed parameter system by input-output linearization
by Nouara HABRACHE, Ahmed MAIDI, Jean-Pierre Corriou
Abstract: In this paper, a control law that enforces the tracking of a boundary controlled output for a bilinear distributed parameter system is developed in the framework of geometric control. The dynamic behavior of the system is described by two weakly coupled linear hyperbolic partial differential equations. The stability of the resulting closed-loop system is investigated based on eigenvalues of the spatial operator
of a weakly coupled system of balance equations. It is shown that, under some reasonable assumptions, the stability condition is related to the choice of the tuning parameter of the control law. The performance of the developed control law is demonstrated, through numerical simulation, in the case of a co-current heat exchanger. The control objective is to control the outlet cold fluid temperature by manipulating its velocity. Both tracking and disturbance rejection problems are considered.
Keywords: partial differential equation; bilinear distributed parameter system; geometric control; characteristic index; exponential stability; co-current heat exchanger
A Non-Linear Coupled-Variables Model for Mass Transfer Modes in MIG-MAG Processes with Experimental Validation
by Paulo Evald, Jusoan Mór, Rodrigo Azzolin, Silvia Botelho
Abstract: Welding processes have relevant importance in many areas of industry, especially in the manufacturing area. The choice of mass transfer mode, to weld metal plates, depends on workpiece structure and its sensibility to the heat input and necessity for material deposition rate. Then, aiming the mass transfer modes in MIG-MAG (Metal Inert Gas - Metal Active Gas) processes utilising pure CO2 as shielding gas, the objective of this paper is present a detailed mathematical modelling for globular and short-circuit transfer modes. The proposed models comprehend a large set of process dynamics, approximating the simulated dynamics very closely to the physical process, which give a high level of credibility for the models. Furthermore, simulations and experimental data are presented to corroborate the validation of both models.
Keywords: Non-linear systems; Time-varying systems; Coupled-parameters systems; Uncertain systems; Gas metal arc welding process.
Robust flux observer and robust block controller design for interior permanent magnet synchronous motor under demagnetisation fault
by Sajjad Shoja-Majidabad, Yashar Zafari
Abstract: This paper deals with rotor flux-linkage estimation in interior permanent magnet synchronous motors. In most applications, the rotor flux is considered as a known constant. However, sharp transients, high loads and high temperatures may cause demagnetisation, which has dominant impact on the interior permanent magnet synchronous motor performance. As a result, estimating the rotor flux-linkage can be helpful to detect and manage demagnetisation fault. To estimate the rotor flux-linkage, a novel integral terminal sliding mode observer is proposed. This fast and robust observer uses stator currents as state variables which can tolerate well against motor uncertainties. This observer can be used to detect or alarm demagnetisation fault for practical applications. However, to keep the motor performance during the demagnetisation fault, a sliding mode block control strategy is proposed for the interior permanent magnet synchronous motor for the first time. The suggested robust controller is composed of a speed control loop (outer-loop) and two stator currents control loops (inner-loops). Owing to rotor saliency, maximum torque per ampere technique is applied for the designed control strategy to provide a reference current. Practical stability of the proposed observer and controller is achieved properly. Finally, comprehensive simulations are carried out to show the effectiveness of the proposed observer and controllers.
Keywords: interior permanent magnet synchronous motor; integral terminal sliding mode observer; sliding mode block control; maximum torque per ampere; demagnetisation fault.
Nonlinear modelling of leader-follower UAV close formation flight with dynamic inversion-based control
by Johnson Yohannan
Abstract: The nonlinear dynamic inversion (DI) control techniques are used in leader-follower UAV dynamics modelling considering new input variables in the present paper. Three separate DI controllers are developed for holding the velocity, heading and flight path angles of both UAVs in a synchronous manner. A numerical simulation is performed at the end for validating this formation control mission of multiple UAVs. The quantitative estimation of reduction in follower drag while in close formation flight is also calculated along with the controller design.
Keywords: dynamic inversion;close formation flight; leader-follower; UAV; induced drag; non-linear control; heading angle; flight path angle; aerodynamic derivatives; up-wash.
Robust speed control design for electric motors using the Kharitonov theorem and genetic algorithms: an experimental study
by Ashraf Saleem, Hisham Soliman, Serein Al-Ratrout, Mahmoud Masoud
Abstract: Electric motor drives are subjected to severe oscillations that might cause motor shaft fatigue and consequent breakdown during system operation. In this paper, a design of robust proportional integral (PI) controller for induction motor (IM) drives is presented. Uncertainties due to different load conditions of the drive system are modelled by a transfer function with interval coefficients. Instead of stabilising an infinite number of polynomials, the Kharitonov theorem is used to design a robust controller by simultaneous stabilisation of only four polynomials. The controller parameters are optimised so that the maximum eigenvalue among the four polynomials is pushed to the left in the complex plane. This is accomplished using Genetic Algorithm (GA) optimisation to achieve the maximum possible rapidity of the system. The proposed controller is tested experimentally using the Hardware-in-the-Loop (HIL) technique. The simulation and experimental results show the validity and effectiveness of the proposed controller as compared to the auto-tuned PID control at different loading conditions.
Keywords: robust digital control; induction motors; Kharitonov theorem; system identification; model-based control.
Identification of rock bolt quality based on improved probabilistic neural network
by Weiguo Di, Mingming Wang, Xiaoyun Sun, Fengning Kang, Hui Xing, Haiqing Zheng, Jianpeng Bian
Abstract: Anchoring technology is widely used in slope, tunnel and underground engineering. However, the rock bolt quality is still a hot problem which is difficult to solve. Considering the shortcoming of pull-out testing, defect identification in a non-destructive way is necessary. In this paper, the signal
Keywords: rock bolt; nondestructive testing; wavelet packet; probabilistic neural network; particle swarm optimisation.
Identification of multi-delay systems using orthogonal hybrid functions in state space environment
by Srimanti Roychoudhury, Anish Deb
Abstract: In this paper, a set of orthogonal hybrid functions (HF) is used for identification of non-homogeneous as well as homogeneous multi-delay systems. The HF set works with function samples and reconstructs a function in a piecewise linear manner. This reduces mean integral square error (MISE) and also computational burden, compared with other methods such as Walsh analysis and block pulse analysis. The presented technique uses a simple algorithm for time-delay system identification. After building up the theory, numerical examples are treated to identify both first- and second-order delay systems. The results obtained are highly reliable to prove the validity of the proposal.
Keywords: orthogonal hybrid functions; multi-delay systems; state space; system identification.
Performance comparison between ultra-local model control, integral sliding mode control and PID control for a coupled tanks system
by Hajer Thabet, Mounir Ayadi, Frédéric Rotella
Abstract: This paper deals with the comparison of robust control approaches for the level water control of a coupled tanks system. A new ultra-local model control (ULMC) approach leading to an adaptive controller is proposed. The parameter identification of the ultra-local model is based on algebraic derivation techniques. The main advantages of this control strategy are its simplicity and robustness. A comparison study with the integral sliding mode control (ISMC) approach is carried out. The perfect knowledge of the output variable degree, which is a standard assumption for sliding modes, is assumed here. The comparison of the simulation results for the proposed adaptive controller with the ISMC controller and the classical PID controller has a better performance in the presence of external perturbations and parameter uncertainties.
Keywords: ultra-local model control; adaptive PID controller; integral sliding mode control; robustness; coupled tanks system.
A new three-dimensional chaotic system with a cloud-shaped curve of equilibrium points, its circuit implementation and sound encryption
by Sundarapandian Vaidyanathan, Aceng Sambas, Sezgin Kacar, Unal Cavusoglu
Abstract: In the chaos literature, significant attention has been paid to chaotic systems with uncountable equilibrium points, such as chaotic systems with line equilibrium, curve equilibrium, etc. This paper reports a novel chaotic system with a cloud-shaped curve of equilibrium points with symmetry properties. A new control law for completely synchronising the new chaotic system with the cloud-shaped equilibrium curve has been established via adaptive integral sliding mode control. Also, an electronic circuit implementation of the theoretical system is designed to check its feasibility. As an engineering application, new results are derived for sound encryption with the new chaotic system.
Keywords: chaos; chaotic systems; chaos synchronisation; sliding mode control; circuit implementation; chaos based encryption; sound encryption.
Accelerated model predictive controller for artificial pancreas
by Mohamed El Hachimi, Abdelhakim Ballouk, Ilyas Khelafa, Abdenasser Baghdad
Abstract: This work is a contribution to the Artificial Pancreas (AP) development by introducing new techniques of control based on an acceleration of reference tracking by using a variable penalisation of the cost function instead of fixed and arbitrary penalisation. Two new functions of the weighting factors are introduced in the formulation of the control algorithm. This method allows a rapid rejection of meal disturbance, a reduction of glucose peak and a complete avoidance of hypoglycemia. The developed controller performances are evaluated by the in silico test, which is equivalent to animal test using the UVa/Padova simulator.
Keywords: artificial pancreas; reference tracking; weighting factors; control algorithm;rndisturbance; hypoglycaemia.
Surface reconstruction algorithm based on local data features
by Zhang Kun, Qiao Shiquan, Gao Kai
Abstract: With the development of reverse engineering devices, the point cloud data, as a common and important form, is applied to the surface reconstruction domain, especially during the non-contact measurement. The 3D scanner is the popular instrument for non-contact measurement as well as point data collection. However, the raw point data is so large, scattered and unordered, the representations of point cloud and reconstruction surface are critical contents in reverse engineering system. This paper provides a new method to describe the point cloud data and proposes the GeoSurface algorithm to complete the surface reconstruction. Firstly, we redefine the the point cloud according to set theory. Secondly, based on the estimation of point cloud feature, the rule of neighbour relationship of data can be deduced. According to this rule, we adopt the KD-tree algorithm to complete data organisation, and improve its searching approach. In addition, the GeoSurface algorithm is proposed in this paper. In this algorithm, the curvature and normal vector are used to estimate local surface features. The GeoSurface algorithm uses an iterative technique to mesh the surface and uses the depth of the KD-tree to control the parameters in the algorithm. Lastly, by using the existing experimental equipment, we verify the GeoSurface algorithm. We adopt three datasets in the experiment, which are collected from the Stanford 3D scanning repository and the 3D laser operated by our lab. The experimental results show the GeoSurface algorithm is an effective algorithm and achieves better results in running time and quality of surface reconstruction compared with greedy and Poisson reconstruction algorithm.
Keywords: point cloud; geometrical features; set theory; surface reconstruction; reverse engineering.
Multi-model approach for 2-DOF control of a non-linear CSTR process
by Dipti Tamboli, Rajan Chile
Abstract: This paper proposes a novel approach to examine the performance of a non-linear Continuous Stirred Tank Reactor (CSTR) at large set point changes where a single model adaptive controller falls short. The efficient closed-loop performance is achieved through multiple models accompanied with a bank of pole placement controllers. To select the best controller at a particular operating point, several multi-model techniques based on different scheduling variables have been adapted. To avoid the multiple switching and discontinuity in switching, the global control signal is calculated by assigning certain weight to each controller. The advantages of proposed method are a satisfactory performance at an unstable operating point as well as at large set point changes with reduced number of models. The effectiveness of the scheme is evaluated and demonstrated through simulation results at different scenarios to achieve 2-DOF control. The comparative study between various techniques shows the superiority of gain scheduler designed on the reference signal for set point tracking and disturbance rejection to tackle the non-linearities of CSTR.
Keywords: CSTR; RLS; pole placement; multiple models; gain scheduler.
Dynamic model of bottom-blown oxygen copper smelting process
by Bin Wang, Zhuo Wang, Yang Jia, Haibin Yu
Abstract: The bottom-blown oxygen copper smelting technology is a new copper concentrate smelting technology. However, in the actual production, it is difficult to measure some key parameters online, such as the matte grade, slag Fe/SiO2, melt temperature, total level, and matte level. A dynamic model is established to predict these parameters online, and is verified using actual production data. The results show that the predicted data and measured data are close, which indicates that the model could effectively predict these key parameters online and be applied to the actual production.
Keywords: bottom-blown oxygen copper smelting process; dynamic model; mass balance; energy balance.
Numerical analysis of H-infinity filter for system parameter identification
by Vassilios Tsachouridis
Abstract: The numerical analysis of the H-infinity filter algorithm for system parameter identification is addressed in this paper. After presenting the filter under study and the convergence characteristics of the algorithm, a first order perturbation analysis is conducted. More specifically, norm-wise bounds are derived for the sensitivities, condition numbers, forward errors, backward errors and rounding errors of the iterative computational operations of the algorithm. Consequently, numerical stability and accuracy rules can be potentially composed as measures of algorithmic reliability and dynamical numerical performance. For exploring the impact of incorporating the specific algorithm dynamics in the numerical analysis, a similar framework is presented for the computed solutions, irrespective of the used algorithm. The paper further exploits the application of the synthesised numerical analysis framework to parameter identification of linear state space systems. Finally some numerical examples are given for demonstration purposes.
Keywords: H-infinity filter; numerical algorithms; error analysis; perturbation analysis.
Wiener model of pressure management for water distribution network
by Shaoyuan Li, Dongming Liu, Jing Wu
Abstract: In this paper, a Wiener model is established to express the nonlinear dynamic pressure management mechanism of water distribution network (WDN). The studied
topology of WDN is pumped into a closed system with pressure control. The hydraulic
element tank plays a key role, and the pressure management model can be divided into two parts according to the feature of the tank being the only dynamic hydraulic component in the whole WDN: the linear dynamic module is to reflect the relationship between the volume (or level) and the flow of inflow/outflow of the tank, and nonlinear static module is to reflect the relationship between the outflows of the tanks and the heads of the terminal consumed nodes, and the linear dynamic block is followed by the static nonlinear block. Moreover, the Wiener model established is compared with the real model in Environmental Protection Agency Network (EPANET), where same consumer heads of the same water distribution network are applied. The theoretical data calculated by the Wiener model are compared with the real data generated by EPANET to show the effectiveness of our proposed modelling method, where three difference scenarios are tested, that is, a WDN with weekday water demands, a WDN including holiday water demands, and a WDN with the consideration of pipeline ages. It can be found that the running situations of the Wiener model are similar to those of actual operation in all of the three cases, which shows that the Wiener model of WDN we established in this paper is computationally efficient and highly accurate.
Keywords: water distribution network; water pressure management; Wiener model;
linear dynamic; nonlinear static.
Mathematical modelling and backstepping adaptive sliding mode control for multi-stage hydraulic cylinder
by Feng Jiangtao, Gao Qinhe, Guan Wenliang, He Zhenxin
Abstract: Multi-stage hydraulic cylinders are widely used in large scale erecting devices. They can provide a longer stroke from an initial package than single stage cylinders. They are divided into telescopic type and synchronous type. However, their structure is complicated. In order to get the characteristics of a multi-stage hydraulic cylinder, a motion model was established based on the node chamber method. The LuGre friction model was improved considering the lubricant film. The contact force model was optimised using the equivalent damping model of the hysteresis factor. Simulations of the erection process driven by telescopic and synchronous hydraulic cylinders were completed. A backstepping adaptive sliding mode controller was designed for the cylinder. The proposed controller has a better performance than the PID controller and ordinary sliding mode controller. The chattering has been reduced by using the saturation function instead of the sign function.
Keywords: telescopic cylinder; synchronous cylinder; erection mechanism; backstepping sliding mode control.
New autonomous scheme of iterative learning control for online implementation
by Leila Noueili
Abstract: The purpose of this paper concerns the design and the implementation of a new autonomous iterative learning control (ILC) scheme for uncertain systems and disturbance rejection. The realization of a real time implementation of three control algorithms applied to a Resistor-Capacitor (RC) circuit is presented. The controller design is characterised as an online control problem. The first is the widely used ILC algorithm (ILC-1), which provides perfect tracking error, and the second ILC (ILC-2) algorithm uses the optimisation based on minimisation of a quadratic criterion in the control error and the input signal. Offline ILC cannot provide a perfect tracking error in every situation. Most noteworthy, non-repeating disturbances and noise degrade ILC performance. The focus is the design and the implementation of a new online autonomous control scheme combining two phases: online error learning and control procedure implementation applied to a Resistor-Capacitor (RC) circuit via the Arduino-Uno microcontroller, which is an advancement in the embedded technology that combines low cost, low consumption, as well as a great performance. The autonomous ILC scheme provides an excellent tradeoff between accuracy, disturbance rejection, response time, low overshoot, stability and robustness. The online ILC controller is presented here as a new approach to compensate the disturbances. The results obtained with the proposed control system and the described methodology to learn from previous errors and signal control inputs to improve the current input control, make it a very suitable solution for this application. It is important to note that fast tracking and high accuracy are achieved as illustrated in the control responses in both ILC-1 and ILC-2 compared with the proportional-integrator controller. Furthermore, the experimental results show the effectiveness of the proposed method.
Keywords: proportional ILC; optimal ILC; Arduino-Uno microcontroller; real time implementation.
Time-varying leader-following consensus of high order multi-agent systems
by Mohammad Ali Ranjbar, Reza Ghasemi, Ali Akramizadeh
Abstract: In this paper, a time-varying leader-following consensus of multi-agent systems under fixed, connected and undirected communication topology is presented. In the proposed method, the dynamics of each agent, including the followers and their corresponding leader, is a linear nth order system. Also, the communication topology between the leader and its neighbours depends on bounded and time-varying functions, assumed to be remained connected as time passes. To tackle this problem, a set of time-varying distributed control laws for each follower agent is designed, based on algebraic graph theory, the algebraic Riccati equation and the Lyapunov direct method. Simulation results indicate the effectiveness of the proposed method and show that convergence to consensus is achieved in a finite time via time-varying distributed control laws.
Keywords: leader-following consensus; multi-agent systems; time-varying topology; linear agent.
Modelling and performance analysis of designed energy-efficient EHA under gravity loads
by Lijing Dong, Hao Yan, Lijun Feng, Qifan Tan
Abstract: Electro-Hydrostatic Actuators (EHA) are highly resembled hydraulic actuators. For specific applications under gravity loads, an innovative structure of EHA using double variable pump and accumulators with designated pressures specified is proposed. The motor speed and the pump displacement can be adjusted synchronously to provide the necessary flow. Consequently, inherent nonlinearity of the two inputs in a multiplication form is involved. Based on analysis of the working principle of the designed EHA, the nonlinear mathematical model precisely describing the multiplication of two coupled inputs is established. The designed EHA balances part of the gravity loads with accumulators, overwhelmingly inducing the energy consumption. Through analysing with reliable and professional hydraulic simulation tool AMESim, the energy-saving performance is demonstrated quantitatively.
Keywords: electro-hydrostatic actuators; energy efficient; gravity heavy loads; mathematical modelling.
Online fault detection for networked control system with unknown network-induced delays
by Mingming Wang, Xiaoyun Sun, Hui Xing, Haiqing Zheng
Abstract: This paper focuses on the online fault detection problem for networked control systems with unknown network-induced delays. In the study, a fault detection model was established for the impact of the unknown network-induced delay. Based on the model, the fault detection filter was constructed, and then the corresponding fault detection problem was converted to an optimisation problem. Finally, a numerical simulation shows that the proposed online fault detection algorithm is not only sensitive to the fault, but also robust to the unknown disturbance caused by the delays.
Keywords: fault detection; networked control system; network-induced delay.
Pedestrian indoor navigation using foot-mounted IMU with multi-sensor data fusion
by Shengkai Liu, Tingli Su, Binbin Wang, Shiyu Peng, Xuebo Jin, Yuting Bai, Chao Dou
Abstract: As a widely used indoor navigation technology, the inertial measurement unit (IMU) based methond has caught considerate research interest. However, owing to the significant and inherent drift of the sensors, it is difficult to get the accuracy trajectory for pedestrian movement estimation. In this paper, a foot-mounted IMU system was used to improve the accuracy of pedestrian trajectory, by fusing information from the multiple sensors. With the Kalman filter combined with the zero-velocity update method, a reasonably accurate pedestrian trajectory was then obtained. Furthermore, some adjustable parameters were introduced to better correct the estimation of position and velocity. The effectiveness of the proposed method was well verified through the indoor experiments, and the long track performance was also tested in a runway verification.
Keywords: IMU; trajectory tracking; multi-sensor data fusion; Kalman filter; zero-velocity update.
On exponential stabilisation for descriptor time-delay systems with nonlinear input via SMC
by Shuqin Wang, Zhen Liu, Cunchen Gao
Abstract: The problem of exponential stabilisation for a class of uncertain descriptor time-delay systems (DTS) is investigated, where both nonlinear input and external disturbance are involved. A novel sliding mode control (SMC) scheme is developed to achieve a stable uncertain system. A delay-free linear sliding surface is first introduced for control design of the DTS. A new adaptive controller is designed to ensure the state trajectories globally converge onto the sliding surface. Furthermore, the considered sliding mode dynamics (SMDs) are derived via equivalent control of the SMC, once the system is in the sliding mode, the proposed criterion can guarantee the SMDs to be exponentially admissible and passive. Finally, the effectiveness of the proposed scheme is verified via an example.
Keywords: descriptor time-delay systems;exponential stability;nonlinear input;sliding mode control.
Improved heuristic algorithm for modern industrial production Scheduling
by Jiang Yongqing, P.A.N. Fucheng
Abstract: Scheduling is one of the core links of modern industrial production. Scheduling needs to be designed according to the characteristics of the production line. In order to optimise the problem of workshop scheduling, the service-oriented programming idea is adopted, with advanced technology to optimise the system development of a mixed flow shop. The system is designed for applications in a distributed network environment. In this paper, an improved heuristic industrial production scheduling method is proposed to solve the scheduling system problem with multiple scheduling tasks, multiple processes, multiple stations, multiple constraints and multiple rules. This method specifies the processing equipment, start time and completion time for each process of the production task. The application method shows that the proposed method can improve the automation and intelligence level of the scheduling process, improve the use rate of equipment and other production resources, and give full play to the enterprise production capacity.
Keywords: production management; modern industry; heuristic; scheduling.
Solvability for nonlinear fractional q-difference equations with nonlocal conditions
by Jufang Wang, Changlong Yu, Yanping Guo
Abstract: In this paper, we study a class of nonlinear fractional q-difference equations
boundary value problems. We obtain the existence and uniqueness of positive solutions for this problem by Banach's contraction mapping principle and Krasnoselskii's fixed point theorem on cone. Finally, we give two examples to illuminate the use of the main results.
Keywords: fractional $q$-difference equations; positive solutions; boundary value problem; fixed point theorem.
Robust adaptive sliding mode control technique for combination synchronisation of non-identical time-delay chaotic systems
by Shikha , Ayub Khan
Abstract: This manuscript presents the methodology in which a robust adaptive sliding mode control technique is used for implementing combination synchronisation of non-identical time-delay chaotic systems. To justify this methodology, a modified Lorenz chaotic time-delay system and a Genesio time-delay system are used. The stability condition for the error dynamics is analysed using Lyapunov stability theory and detailed mathematical theory. Numerical simulations are carried out to demonstrate the efficiency of the proposed approach that supports the analytical results.
Keywords: time-delay chaotic system; combination synchronisation; robust adaptive sliding mode control; Lyapunov stability theory.
Towards a unified stability analysis of continuous-time T-S model based fuzzy control systems
by Weicun Zhang
Abstract: This paper is intended to develop a unified stability analysis framework for a general closed-loop continuous-time T-S model based fuzzy control (TSFC) system, which consists of the parallel distributed compensation (PDC) controller and the real plant instead of the T-S fuzzy model. The plant to be controlled may be a linear time-invariant, linear parameter jump, or nonlinear time-varying system. As an alternative to Lyapunov function based approach, virtual equivalent system (VES) approach is introduced. The stability of a TSFC system is identical to that of the corresponding VES.
Keywords: T-S model based fuzzy control; stability; virtual equivalent system.
Robust mixed performance for uncertain Takagi-Sugeno fuzzy time-delay systems with linear fractional perturbations
by Chang-Hua Lien, Sundarapandian Vaidyanathan, Ker-Wei Yu, Hao-Chin Chang
Abstract: The robust mixed H2/Hinf. performance for Takagi-Sugeno (T-S) fuzzy systems with time delay and linear fractional perturbations is considered in this paper. Some delay-dependent conditions have been proposed to guarantee the mixed performance of uncertain fuzzy time-delay systems. The LMI optimisation approach is used to find the minimisation of performance measure. Some numerical simulations are illustrated to show the significant improvement over some previous results.
Keywords: mixed H2/Hinf. performance; Takagi-Sugeno fuzzy systems; time delay; linear fractional perturbations.
Iterative linear quadratic regulator control for quadrotors leader-follower formation flight
by Wesam Jasim, Dongbing Gu
Abstract: This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotor leader-follower formation. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR controller to successfully track different paths by the leader and maintain the relative distance between the leader and the follower by the follower. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.
Keywords: iLQR controller; LQR controller; optimal control; leader-follower formation; unit quaternion; UAV quadrotors.
Adaptive backstepping control of multi-mobile manipulators handling a rigid object in coordination
by Abdelkrim Brahmi, Maarouf Saad, Guy Gauthier, Wen-Hong Zhu, Jawhar Ghommam
Abstract: This paper presents an adaptive backstepping control scheme applied to a group of mobile manipulator robots transporting a rigid object in coordination. All the dynamic parameters of the robotic system, including the handled object and the mobile manipulators, are assumed to be unknown but constant. The problem of uncertain parameters is resolved by using the virtual decomposition approach (VDC). This approach was originally applied to multiple manipulator robot systems. In this paper, the VDC approach is combined with backstepping control to ensure a good position tracking. The controller developed in this work ensures that the position error in the workspace converges to zero, and that the internal force error is bounded. The global stability of the entire system is proven based on the appropriate choice of Lyapunov function using virtual stability of each subsystem, based on the principle of the virtual work. An experimental validation is carried out for two mobile manipulators moving a rigid object in order to show the effectiveness of the proposed approach.
Keywords: backstepping control; adaptive control; virtual decomposition approach; multiple mobile manipulator robots.
Accuracy control in Monte Carlo simulations of particle breakage
by Jherna Devi, Gregor Kotalczyk, Einar Kruis
Abstract: Monte Carlo (MC) methods are an important tool for the numerical solution of the population balance equation, allowing the optimisation and control of particulate processes on laboratory or plant scales. We investigate in this work a family of MC methods for particle breakage proposed by Kotalczyk et al., Powder Technology (2017), 317, pp. 417-429. The authors reported that specific breakage schemes (defined by a combination factor R) allow to render the full particle size distribution. They also showed that specific ranges of the combination factor R might lead to severe systematic errors, but did not investigate measures of control or prevention. In this paper, a strategy which allows to estimate the magnitude of the systematic error from the simulation data is presented. It is also shown how the simulation parameters can be set in order to keep the systematic error at an acceptable level.
Keywords: Monte Carlo; population balance; weighted particles; simulation; GPU; breakage; optimisation; control.
H performance of continuous switched time-delay systems with sector and norm bounded nonlinearities
by Chang-Hua Lien, Sundarapandian Vaidyanathan, Ker-Wei Yu, Hao-Chin Chang
Abstract: In this paper, the exponential stabilisation and H∞ performance analysis for switched systems with time-varying interval delay and multiple nonlinearities by switching rule design are considered. H∞ performance is guaranteed by the proposed LMI delay-dependent criteria via the selection of the switching rule. The selected scheme of switching rule is developed to improve the difficulty for the generalisation of the proposed main results. Finally, some examples are presented to show the reduced conservativeness of our developed results.
Keywords: H∞ performance; Park inequality; switched system; selection of switching rule; time-varying interval delay; sector bounded nonlinearities; norm bounded nonlinearities.
Comparision of Hybrid Path Planning Approaches for Vehicles in 3D Non-Deterministic Environments
by Denis Beloglazov, Valery Finaev, Mikhail Medvedev, Igor Shapovalov, Viktor Soloviev
Abstract: The article presents the development and analysis of hybrid path planning systems for vehicles. Two types of planner structures have been defined. In the first type of systems, several basic path planning methods operate together. In the systems of the second type, parameters and initial data of one basic method are modified by additional algorithms. We developed the controller that solves positioning and path-following problems with a high accuracy. Hybrid path-planning systems are developed for a hexacopter based on the virtual fields method and fuzzy logic. In the first synthesized system, the special algorithm of sensor data analysis modifies an initial data to use the virtual fields method.
Keywords: hybrid planner; virtual fields; fuzzy logic; obstacle points cloud analysis; hexacopter control; position-path controller
NARMAX model identification using a randomised approach
by Pedro Retes
Abstract: Structure selection is one of the most critical steps in nonlinear system identification. A large family of methods, based on model prediction error, uses concepts and tools from linear algebra. Other methods, based on model simulation error, have to deal with non-convex optimisation problems. More recently a family of methods has ben put forward that has probabilistic setting. The Randomized algorithm for Model Structure Selection (RaMSS) belongs to this family and it has been shown to be effective to select regressors for NARX models. In the present paper, such a method is extended to cope with NARMAX models. The performance of the proposed method is illustrated using simulated and experimental data. It is shown that the proposed method is capable of correctly selecting model structures from simulation data. The method was also applied to experimental data with successful results.
Keywords: NARMAX; non-linear models; ELS; OLS; RaMSS; NARX; system identification; parameter estimation.
Modelling of gene signal attribute reduction based on neighbourhood granulation and rough approximation
by Jian Xue, Fu Liu, Jing Bai, Tao Hou
Abstract: The update of high-throughput sequencing technology has led to the dramatic increase in the number of sequenced meta-genomic DNA sequences. However, extracting a nearly 10,000-dimensional digital signature as a species tag will inevitably bring about tremendous computational load. Therefore, how to reduce the macro features of macro-genomic DNA and how to extract and select the subset with the best characteristics as a species tag has become a research direction of bio-informatics. In this paper, we use neighbourhood granulation and rough approximation theory modelling to study the method of attribute reduction of meta-genomic DNA fragments and to deduce the digital features of meta-genome at the 'genus' classification. The results show that this method can effectively screen out representative species tags and improve classification efficiency.
Keywords: meta genomics; attribute reduction; neighborhood rough set; species classification; K-mer frequency.
On Peng's type maximum principle for optimal control of mean-field stochastic differential equations with jump processes
by Shahlar Meherrem, Mokhtar Hafayed, Syed Abbas
Abstract: In this paper, we investigate the Peng's type optimal control problems for stochastic differential equations of mean-field type with jump processes. The coefficients of the system contains not only the state process but also its marginal distribution through their expected values. We assume that the control set is a general open set that is not necessary convex. The control variable is allowed to enter into both diffusion and jump terms. We extend the maximum principle of Buckdahn et al. (Appl Math. Optim. 64(2), 197-216, 2011) to jump case.
Keywords: mean-field jump systems; stochastic optimal control; Peng's maximum principle; spike variation method; second-order adjoint equation; Poisson martingale measure.
Optimal torque vectoring control for distributed drive electric vehicle
by Wei Xu, Zhijun Fu, Weidong Xie, Anqing He, Yong Xiao, Bin Li
Abstract: A novel optimal torque vectoring control (TVC) strategy is proposed in this paper to enhance the lateral stability of a dual-motor rear-wheel drive electric vehicle. The structure of the optimal TVC consists of three parts, i.e. pre-processor, model-following controller and post-processor. Unlike the commonly used linear single track vehicle model, an accurate nonlinear vehicle model is built in the pre-processor based on the Magic Formula tyre model. The model-following controller is responsible for producing the corrective yaw moment by a two-dimensional gain scheduling method related to the vehicle longitudinal velocity and lateral acceleration. This optimal yaw moment controller, consisting of the steady-state control law and the optimal feedback control law, is developed to compensate the nonlinear property induced by time-varying tyre cornering stiffness. In the post processor, torque vectoring allocation strategies are presented considering the constraints of motor peak torque and tyre friction. Co-simulation results of the CarSim and LabVIEW under two driving manoeuvres (step steering and skid pad track) illustrate that the lateral and longitudinal performance of the vehicle is greatly improved and experimental results of hardware-in-the-loop (HIL) proves that the control system can be well used in real-time.
Keywords: optimal control; torque vectoring; lateral stability; Magic Formula; co-simulation; HIL.
An improved energy-aware and self-adaptive deployment method for autonomous underwater vehicles
by Chunlai Peng, Tao Wang
Abstract: Autonomous underwater vehicles (AUVs) are special mobile robots travelling underwater and perform dangerous tasks for humans in unknown mission areas. However, there are two critical issues when deploying AUVs. First, these algorithms do not optimise the travelling distances of AUVs and hence will lead to excessive energy depletion. Second, these deployment models rarely consider the available energy variations among AUVs in the task execution process. For this reason, an energy-aware and self-adaptive deployment method is presented for a group of AUVs taking collaborative tasks. First, the movement priority of AUVs is considered according to their positions during the deployment process. Second, an improved virtual force algorithm is proposed to obtain the initial deployment scheme. In addition, a self-adaptive deployment strategy is presented for redeploying the AUVs when the available energy of some AUVs has fallen below a certain threshold. Simulation results with 10 AUVs demonstrate that the proposed method greatly decreases energy consumption (evaluated by the movement distances of AUVs) by about 30% than its traditional counterpart and it can redeploy AUVs adaptively and rapidly.
Keywords: autonomous underwater vehicles; Voronoi diagram; energy-awareness; self-adaptive deployment; unknown environment.
Stabilisation of time delay systems with nonlinear disturbances using sliding mode control
by Adrian E. Onyeka, Xing-Gang Yan, Zehui Mao, Jianqiu Mu
Abstract: This paper focuses on a class of control systems with time delay states and time delay nonlinear disturbances using sliding mode techniques. Both matched and mismatched uncertainties are considered, which are assumed to be bounded by known nonlinear functions. The bounds are used in the control design and analysis to enhance robustness. A sliding function is designed and a set of sufficient conditions is derived to guarantee the asymptotic stability of the corresponding sliding motion by using the Lyapunov-Razumikhin approach, which allows large time-varying delay with fast changing rate. A delay-dependent sliding mode control is synthesised to drive the system to the sliding surface in finite time and maintain a sliding motion thereafter. Effectiveness of the proposed method is demonstrated via a case study on a continuous stirred tank reactor system.
Keywords: stabilisation; sliding mode control; time delay; uncertain systems; Lyapunov-Razumikhin approach.
Coupling vibration analysis of the elastics structure with liquid
by Jin Yan
Abstract: The equations of the structure motions are accomplished in terms of the displacement form, and the liquid formulations are expressed by pressure, with or without considering the effect of sloshing. The unknown coefficients in the two domains are expanded into velocity potential and vibration functions by the Galerkins method. The coupled vibration of the elastics baffle with two sides fluid, in a rigid tank, is also carried out by finite element method (FEM), which regards the structure and fluid element global degrees of freedoms as row index and column index, and the coupled matrix is assembled to the global matrix. Finally, the coupled frequencies of simple supported beam and liquid are computed, which are in good agreement with the FEM results. The effects of the liquid filling height and beam flexibility on the slosh response are also investigated. The baffles with two sides fluid vibration numerical results by the proposed FEM, are compared with the test example, which agree well.
Keywords: elastics structure; liquid; coupling vibration; Galerkins method; free surface; FEM.
Stochastic gradient based particle filtering method for ARX models with nonlinear communication output submodel
by Jianxia Feng, Donglei Lu
Abstract: This paper develops a stochastic gradient based modified particle filter algorithm for a AutoRegressive eXogenous (ARX) model with nonlinear communication output submodel.The outputs of the ARX model are transmitted over a nonlinear communication network, while the outputs of the communication network are available. Based on the modified particle filter and the available outputs, the outputs of the ARX model can be computed, and then the unknown parameters can be estimated by the stochastic gradient algorithm. The simulation results demonstrate that the stochastic gradient based particle filter algorithm is effective.
Keywords: System identification, Stochastic gradient, Particle filter, Missing outputs, ARX model
Thermal Stress Deformation Prediction for Rotary Air-preheater Rotor using Deep Learning Approach
by Jing Xin, Rong Yu, Ding Liu, Youmin Zhang
Abstract: Failures often occur in the seal clearance measuring sensor due to the harsh operating conditions of the rotary air-preheater in power plant boilers. Therefore, it is necessary to predict the rotor deformation to eliminate the effects of failures on the gap control system. An air-preheater rotor thermal stress deformation prediction method is proposed in this paper based on deep learning. Firstly, a stacked auto-encoder (SAE) is constructed and trained to learn the feature information which is hidden within the input data (the temperature of flue gas side inlet, air side outlet, flue gas side outlet, air side inlet); then, an Elman neural network is constructed and trained using the output of the encoder part of the well trained stacked auto-encoder to predict rotor deformation. Simulation and experimental results show that the proposed SAE-Elman prediction method can obtain the effective feature representation and has better prediction precision compared with other traditional prediction methods.
Keywords: deep learning; stacked Auto-encoder; rotary air-preheater; thermal stress deformation predicti
Output Feedback Nonlinear Control of Power System Under Large Penetration of Renewable Energy Sources
by Hassan EL FADIL, Fouad Giri
Abstract: This paper deals with the problem of stability analysis and controlling a power system in which a synchronous generator and renewable energy sources supply the power to an infinite bus. Firstly the investigation of the existence of the equilibrium points of the system and their stability are presented. For this problem, we derive a sufficient condition on the renewable energy current for the existence of the equilibrium points. In addition, we analyze the stability of the equilibrium points, and show that there is only one equilibrium points which is stable. These results clarify the impact of the penetration of renewable energy sources on the existence of the stable equilibrium points of the system. Secondly, the focus is made on elaborating an output feedback controller, combining a state observer and a nonlinear control law that stabilizes the closed loop system whatever the current of renewable energy sources. Numerical simulations are given in order to show the effectiveness of all theoretical results.
Keywords: Power system; renewable energy; stability analysis; nonlinear control; nonlinear observer; output feedback control.
Research on the Control Algorithms of Human-thinking Simulated Control
by Peijin Wang
Abstract: Human-Thinking Simulated Control is proposed firstly according to the human cognition and human control thinking mechanism many years ago. Human control thinking includes image intuitive reasoning control thinking, abstract logical inference control thinking and inspiration inference control thinking. The methods of simulating the image intuitive reasoning control thinking and the abstract logical inference control thinking are discussed in the paper. Some cases study prove that the methods are better for simulating human control thinking and the test results are better than that of traditional control methods.
Keywords: Human thinking; intelligent control; control thinking; Human-Thinking Simulated Control
MLNMF: multi-label learning based on non-negative matrix factorisation
by Yu Han, Cheng Shao, ShouTao Yang, Weiwei Deng
Abstract: Multi-label learning deals with the problem where each instance is associated with a set of labels. The task is to predict the label sets of unseen instances through training the instances with known label sets. Existing approaches make predictions by learning from the distribution of multi-label instances. However, the direct relevance between features and labels has often been overlooked in the literature. In this paper, a multi-label learning approach named MLNMF is presented, which is derived from the traditional non-negative matrix factorisation algorithm. In detail, first propose to generate a label probability predict model (LPPM) utilising the NMF method to capture the direct relevance between features and labels. Then exploit the decision stump method to generate a classifier for each label. The proposed method is a first-order approach which assumes that each label is independent with each other. Compared to the existing approaches for multi-label learning, the proposed approach is advantageous which is able to explore the direct correlation between features and labels and the operating efficiency is much higher than other algorithms. The experimental results on a total of nine benchmark datasets illustrate the competitiveness of MLNMF against some well-established multi-label learning algorithms.
Keywords: multi-label learning; non-negative matrix factorisation; algorithm; predict model; multi-label learning.
High-performance torque controller design for AC driving 4WD electric vehicle in two time scales
by Zhi-Jun Fu, Bin Li, Xiao-Bin Ning
Abstract: In this paper, a novel torque control method of AC induction motor in two time scales is proposed for 4WD electric vehicles. A two-time-scale sliding-mode control (SMC) observer and a SMC controller are synthesised to ensure high-performance torque control. Two time scales are considered based on the natural time scale separation existed in the AC induction motor driving system, i.e., rotor flux and speed corresponding to the slow dynamics and the stator current corresponding to the fast dynamics. The convergence property of the controller is considered when performing the observer design rather than the conventional control method where the controller and observer are designed separately. Moreover, the more advanced space vector modulation (SVM) technology instead of the sinusoidal pulse width modulation (SPWM) method used in the conventional SMC is also introduced in the proposed method to achieve minimum torque ripple. The effectiveness of the proposed torque control method is illustrated through simulations on a 4WD electric vehicle. Simulation results illustrate the improved performance compared with the conventional SMC method.
Keywords: torque control; 4WD; two time scales; electric vehicle; AC induction motor.
Bolt quality testing research using weighted fusion algorithm based on correlation function
by Xiaoyun Sun, Hui Xing, Guang Han, Jiulong Cheng, Yongbang Yuan, Jianpeng Bian, Haiqing Zheng, Mingming Wang
Abstract: Bolt length is an important factor for quality evaluation of anchors. Because of the harsh detection environment and the interference caused by instruments, bolt testing signal contains a lot of noises that make it difficult to analyse and predict the parameters of anchor bolts accurately. In this paper, a non-destructive method based on information fusion of pseudo random signals is presented for bolt quality testing. After pseudo-random signals are generated by multiple sources, weighted fusion algorithm based on correlation function is proposed for fusion processing. Compared with the D-S fusion algorithm and average weighted fusion approach, the correlation fusion is verified to have higher accuracy and better retention of frequency characteristic. Finally, this proposed approach is proved to be more suitable for random signal fusion.
Keywords: anchor bolt modelling; non-destructive testing; D-S fusion algorithm; weighted fusion based on correlation function.
Fault diagnosis and model predictive fault tolerant control for stochastic distribution collaborative systems
by Yunfeng Kang, Ling Zhao, Lina Yao
Abstract: This paper presents a fault-tolerant control scheme for a class of stochastic distribution collaborative control systems, which are composed of two subsystems connected in series to complete the target. The output of the whole system is the output probability density function (PDF) of the second subsystem. To diagnose the fault in the first subsystem, an adaptive diagnostic observer and linear matrix inequality (LMI) technique are used to obtain the adaptive tuning law to estimate the fault. When fault occurs, the fault itself can not be compensated in the first subsystem and a model predictive controller is designed in the second subsystem to compensate the fault, making the post-fault output PDF still track the desired PDF as close as possible. A simulated example is given and desired results have been obtained.
Keywords: stochastic distribution collaborative control systems; fault diagnosis; FD; fault tolerant control; FTC; model predictive control; MPC; linear matrix inequality; LMI.
Command filter-based adaptive neural control for permanent magnet synchronous motor stochastic nonlinear systems with input saturation
by Yuxi Han, Jinpeng Yu, Zhen Liu, Lin Zhao
Abstract: For solving the problems of stochastic disturbance and input saturation existing in permanent magnet synchronous motors (PMSMs) drive systems, a command filter-based adaptive neural control method is proposed in this paper. Firstly, the neural networks technique is utilised to approximate unknown nonlinear functions. Then, the command filtered controller is constructed to avoid the 'explosion of complexity' inherent in the classic backstepping control and the error compensation mechanism is introduced to reduce the error caused by command filter. Moreover, the adaptive backstepping method is utilised to design controllers to assure that all signals are bounded in the closed-loop systems. Finally, the effectiveness of the approach is certified by the given simulation results.
Keywords: adaptive neural control; backstepping; permanent magnet synchronous motors; PMSMs; command filter; stochastic nonlinear systems.
Model-based sliding functions design for sliding mode robot control
by Charles Fallaha, Maarouf Saad
Abstract: This paper introduces a novel manifold design for sliding mode control, applicable to second-order mechanical systems in which nonlinear dynamics can be formalised into that of robotic manipulators. The new approach shows that model-based sliding manifold design substantially simplifies the torque control law, which ultimately becomes linear in terms of joint angles and rates. Additionally, this approach allows the decoupling of the chattering effect on the torque inputs on each axis. A new property related to the gravity term is introduced and is used for stability analysis and model validation. Simulation results compare the introduced approach to the conventional linear manifold design and demonstrate that the new approach reduces transient constraints on torque input and is more robust to matched uncertainties for low inertia robots.
Keywords: sliding mode control; nonlinear control; robot control; nonlinear sliding manifolds; chattering.
Adaptive decentralised sliding mode controller and observer for asynchronous nonlinear large-scale systems with backlash
by Ahmad Taher Azar, Fernando E. Serrano
Abstract: In this article an adaptive decentralised sliding mode controller and observer for asynchronous nonlinear large-scale systems with backlash is proposed. In the literature, only the synchronous case for input nonlinearities such as dead-zone and saturation is found. In this article, the asynchronous case for systems with backlash is studied considering the backlash effect. Owing to the complexity of the backlash nonlinearity, an adaptive decentralised controller is proposed because of the capability of this strategy to deal with uncertainties and to improve the system performance when this nonlinearity is found. Additionally, a decentralised sliding mode observer is proposed in order to estimate the states of the system.
Keywords: decentralised control; switched systems; sliding mode control; asynchronous control.
Special Issue on: ICEE2015 Signals and System Modelling, Design and Simulation
Protection of 25kV Electrified railway system
by farid Achouri, Imed eddine Achouri, Mabrouk Khemliche
Abstract: Improving a reliability of electrified railway operation system requires protection against overvoltage, particularly those of atmospheric origin. The most serious threat to the traction system is lightning when it strike the mast or conductors. The ZnO arresters are used to protect a system from this phenomenon. In the present investigation the system under study is developed and each element is represented by a model corresponding in EMTP program and some elements are modeled using the Models section in ATP EMTP. Protective effect of the surge arrester and discharge current which passes through it is analyzed and discussed in case lightning strikes a mast. The simulation results have shown that the surge arrester reduce overvoltage in primary power transformer traction below the Basic Insulation Level BIL, under critical conditions.
Keywords: Railway traction network; Overvoltage; Lightning; Modelling; Simulation; Surge arrester ZnO.
Special Issue on: ICMIC2016 Modelling and Control
Sensorless High-order Super Twisting Sliding Modes Vector Control for Induction Motor Drive with Adaptive Speed Observer.
by Horch Mohamed, Boumédiène Abdelmadjid, Baghli Lotfi
Abstract: This paper proposes a high-order super twisting sliding mode control method applied to an induction motor fed by a power voltage source without speed sensor. Based on the vector control principle, high-order super twisting sliding mode controllers in speed loop and flux loop are designed respectively. The super twisting sliding mode control is utilized to improve the response speed and robustness of motor control systems. Meanwhile, high-order sliding modes are adopted to eliminate the chattering phenomenon. We also present the mechanism of adaptive super twisting speed and rotor flux observers with the only assumption that from stator voltages and currents are measurable. The objective is to improve the speed control, the rotor flux control under load torque disturbances and parameter variations.The simulation results prove clearly a good robustness against load torque disturbances, the estimated fluxes and the rotor speed converge to their real values. Our study is close to reality; all carried out simulations are based on real models simulated within the MATLAB SYMPOWER SYSTEM environment in continuous time.
Keywords: nonlinear systems; field oriented control; induction motor drive; robustness; super twisting sliding mode; sensorless drive.
Novel Adaptive Iterative Observer Based on Integral Backstepping Control of a Wearable Robotic Exoskeleton
by brahim brahmi, Maarouf Saad, Cristobal Ochoa-Luna , Mohammad Habibur Rahman, Abdelkrim Brahmi
Abstract: In this paper, an integral backstepping control combined with an iterative estimator and a Jacobian observer of external forces is used to take into account the dynamics' uncertainties of an exoskeleton robot arm. The exoskeleton robot carries the upper limb of the subject to perform a passive physical therapy. The user’s force is thus considered as an external disturbance. Additionally, an accurate modelization of the dynamic model of the 7-DOFs exoskeleton robot is not available due to its complicated mechanical structure. In such a case, the system may be subject to modeling uncertainty. In order to reduce the uncertainties and external disturbances effects, a robust integral backstepping control and a Jacobian force observer are used. A Lyapunov function is selected to prove the closed loop stability of the system. Experimental results show the effectiveness and feasibility of the designed controller to the uncertain robot system.
Keywords: Backstepping control; Iterative control; Force observer; Physical therapy; uncertainty
Hybrid Chaotic Synchronization between Identical and Non-Identical Fractional-Order Systems
by Abir Lassoued, Olfa Boubaker
Abstract: In this paper, a chaotic hybrid synchronization (HS) for multiple fractional-
order (FO) systems coupled with ring connection is proposed. For such schema, the
complete synchronization (CS) and the complete anti-synchronization (AS) should coexist
in the same time under designed control laws. It will be ascertain, that integer-
order controllers are adept to synchronize asymptotically coupled FO systems. In
order to prove the effectiveness of the synchronization schema, two cases studies are
considered where multiple FO identical systems and multiple non-identical FO systems are
synchronized, respectively. Finally, numerical simulations illustrate the well achievement
of the synchronization problem under the designed control laws.
Keywords: Fractional-order; Hybrid Synchronization; Ring connection; Anti-synchronization; Complete synchronization.
Chaos Synchronization of Two different PMSMs Via a fractional-order sliding mode controller
by Amina BOUBELLOUTA, Abdesselem Boulkroune
Abstract: This paper deals with the design problem of a fractional-order sliding mode control to synchronize two different chaotic permanent magnet synchronous motors (PMSM). By constructing fractional-order sliding mode surfaces, it is proved that the corresponding synchronization errors are Mittag-Leffler stable. The simulation results show that the proposed controller is strongly robust against the parametric variations, modelling uncertainties and unknown external disturbances, and can significantly reduce the chattering level.
Keywords: Fractional-order sliding surface; sliding mode control; chaotic PMSM; chaos synchronization
Special Issue on: ICMIC2017 Advanced Modelling and Control for
Modelling and fault tolerance analysis of triplex redundancy servo valve
by Hao Yan, Lei Yao, Li-bo Qiu, Bo Chen, Li-jing Dong
Abstract: To investigate the stability and reliability of the triplex redundancy servo valve, a complete theoretical model needs to be built. By constructing the mathematical models of the torque motor, the armature-flapper assembly and the spool valve, the theoretical model of the triplex redundancy servo valve is deduced and the dynamic simulation method is obtained. Then, its dynamic and static characteristics are simulated and analysed by Simulink and AMEsim, respectively. The triplex redundancy servo valve may often suffer from two faults, the signals broken circuit and full bias. Simulations show that the faults will lead to the decrease of the valves working capability, the deviation of the valves output, and the decline of the dynamic performance. However, the valve can still work stably and the output of the hydraulic system will not be much affected, which show the valves favourable fault tolerance capability. Finally, the validity of the theoretical model for fault analysis is verified by an experiment.
Keywords: servo valve; triplex redundancy; fault; AMEsim; simulation.
A model-based implementation of an MPPT technique and a control system for a variable speed wind turbine PMSG
by Najmeh Rezaei, Kamyar Mehran, Calum Cossar
Abstract: This paper proposes a model-based control system for a wind energy conversion system (WECS) using a direct driven permanent magnet synchronous generator (D-PMSG). The generator is connected to the grid via a back-to-back pulse-width modulation (PWM) converter with a switching frequency of 10KHz. The integrated system model is developed in Matlab/Simulink and is based on the practical setup parameters to fully and accurately mimic the behaviour of the experimental system. A PI controller provides the generator with an optimum speed via an aerodynamic model of the wind turbine and can be readily employed for the practical setup using the designed parameters in the simulation model. A maximum power point tracking (MPPT) algorithm is further developed to ensure the maximum power captured from a wind turbine. The MPPT algorithm is simplified to reduce the computational time required for the real-time simulation.
Keywords: MPPT; PI controller; PMSG; Simulink; WECS; wind energy conversion; wind power; wind speed; wind turbine.
A recursive discrete Kalman filter for the generation of reference signal to UPQC with unbalanced and distorted supply conditions
by Venkatesh Kumar
Abstract: This paper deals with the development of a robust control technology adapting Kalman filter in order to address the problems arising in power quality. This methodology makes use of three-phase three-wire Unified Power Quality Conditioner (UPQC) under unbalanced and distorted supply conditions. In spite of harmonics and frequency oscillation, the Kalman filter determines the amplitude, phase angle and frequency of load currents and source voltages. The main idea are to use Kalman filtering algorithm to acquire the fundamental components of load current and source voltage and use the least squares method, which is relatively simple and fast. The proposed robust Kalman filter based UPQC system mitigated issues such as voltage sag, voltage swell, harmonics distortions (voltage and current), and unbalanced supply voltage and power factor. The results are justified using the MATLAB/Simulink software to support the Kalman filter based control algorithm under steady state and dynamic operating conditions.
Keywords: unified power quality conditioner; synchronous reference frame; Kalman filter; phase locked loop.
Combining recursive projection and dynamic programming technique in multi UAVs formation anomaly detection
by Wang Jianhong
Abstract: To deal with the problem of anomaly detection in multi UAVs formation, and simplify the complexity of hypothesis testing or probability inequalities, the anomaly detection problem can be transformed to identify some unknown parameters process. To avoid a statistical description on measurement noise, a worthwhile alternative is the bounded noise characterisation. In the presence of bounded noise, the projection algorithm with dead zone and its modified form are proposed to identify the unknown parameters, such that the robustness of projection algorithm can be enhanced by increasing a dead zone. Furthermore, dynamic programming technique is introduced to balance the desire for lower present cost with the undesirability of high future cost in determining the anomaly detector, then the cost of collecting new observations and the higher probability of accepting the wrong hypothesis can be compensated. A numerical example illustrates the characteristic of the anomaly detection problem.
Keywords: multi UAVs formation; anomaly detection; projection algorithm; dynamic programming; dead zone.
Attitude tracking control of rigid spacecraft with disturbance compensation
by Zhongtian Chen, Qiang Chen, Meiling Tao, Xiongxiong He
Abstract: In this paper, a fast power reaching law based sliding mode control with disturbance observer is presented to solve the attitude tracking control problem for rigid spacecraft with the existence of inertia uncertainty and external disturbance. A disturbance observer is presented to estimate the lumped disturbance with bounded change rate. Then, a sliding mode controller is designed based on the fast power reaching law with considering disturbance estimation to ensure the convergence of the attitude and angular velocity tracking errors. Lyapunov theorem is given to verify the stability of the closed-loop system. The effectiveness and feasibility of the proposed scheme are illustrated by the simulation results.
Keywords: rigid spacecraft; disturbance observer; sliding mode control; fast power reaching law.
Optimal storage sizing of energy storage for peak shaving in presence of uncertainties in distributed energy management systems
by Yue Li, Qinmin Yang
Abstract: The rapid development of eco-friendly technologies, such as energy storage systems (ESS) and peak-shaving technology in smart grid, plays a significant role and shapes the future electricity consumption patterns. Distributed energy management systems (DEMS) can be used to shave the peak load and reduce the users' electricity tariff. In this paper, a robust analytical method is presented to determine the size of ESS and its scheduling strategy. Firstly, Extreme Learning Machine (ELM) and k-means algorithms are employed to classify customers into groups according to their characteristics. For each group, a support vector regression (SVR) model is developed for improving accuracy of load forecast. The whole storage system is then divided into schedule-based capacity and emergency capacity for different optimal objectives. A mixed integer linear programming (MILP) model considering the reliability constraints, peak-shaving requirement, and linearisation method is constructed to optimise the management of the DEMS. Verification and comparison studies demonstrate the effectiveness of the proposed scheme.
Keywords: distributed energy management system; short-term load forecasting; energy storage system; mixed integer linear programming.
Special Issue on: ICMIC2017 Advanced Modelling and Control forElectrical-Mechanical Systems
Modelling and attitude control of novel multi-ducted-fan aerial vehicle in forward flight
by Lu Lin, Yue Ma, Wanming Chen
Abstract: Multi-ducted-fan aerial vehicle (MDFAV) is a novel platform for future transportation with promising prospects, which presents brand new challenges to the modelling and control approaches. In this paper, a comprehensive flight dynamical model of MDFAV is established using the aerodynamics principles and classical rigid body dynamics theory aiming to balance the complexity and covering necessary important dynamical behaviour of MDFAV, which is converted into state space by linearisation at the specific speed in forward flight mode in the following step. Subsequently a dual closed loop PID controller is put forward to keep flight fast and stable with the key coefficients tuned by non-smooth parameters optimisation method. The software and hardware of flight controller are designed for flight test of MDFAV systematically. Experiment results demonstrate excellent tracking performance and robustness, and at the same time, environment disturbances are suppressed effectively.
Keywords: multi-ducted-fan aerial vehicle; dual closed loop PID; non-smooth optimisation.
Monitoring the lack of grease condition of rolling bearing using acoustic emission
by Kaiqiang Wang, Xiaoqin Liu, Xing Wu, Zhenjun Zhu
Abstract: Bearings are vital parts of machines, and their condition is often critical to the operation or process. Lubricants such as grease can present a film between the bearing surfaces and minimise the friction and wear. Lack of lubricant may lead to ineffective performance or malfunction of the bearing. Therefore, in order to avoid unexpected breakdowns, reliable lubrication monitoring techniques are demanded. Acoustic Emission (AE) technology can detect the friction between moving parts in the machines. The object of the paper is to evaluate the grease amount in the rolling element bearing with AE signals. Four parameters of AE are studied, including event count rate, ring count per event, energy rate, and RMS. The first three parameters are derived from AE parameter analysis, and RMS is calculated directly on the continuously sampled signal. Eight amounts of the grease in the same bearing are tested respectively. Experiments on grease consumption with running time are also carried out. According to the results, RMS and energy rate can be used to estimate the remaining amount of the lubricant. The method is also verified by field tests on articulated industrial robots.
Keywords: acoustic emission; lack of lubricant; rolling bearings; condition monitoring.
Kinematic calibration for industrial robots using articulated arm coordinate machines
by Guanbin Gao
Abstract: To improve the position accuracy of industrial robots, a novel kinematic model and calibration method using articulated arm coordinate machines (AACMM) is proposed in this paper. The end of the industrial robot (the active arm) is connected to the probe of an AACMM (the passive arm), thus forming a closed kinematic chain. Therefore, the position of the industrial robots end can be derived from the AACMM after coordinate transformation. The coordinate systems of the double arms were established, based on which the mapping of the joint angles and the position of the end were derived as well as the nominal value of the kinematic parameters of the industrial robot. A two-step search method was presented for kinematic parameter identification of the industrial robot. The first step is to use genetic algorithm (GA) performing the global search. The result obtained in the first step is used as the initial solution of tabu search algorithm (TSA) in the second step to perform local search in a small range, and then the identified kinematic parameters can be reached. The identified kinematic parameters were used to compensate the errors of the nominal kinematic parameters in the controller of the industrial robot. Experiments were conducted to verify the calibration method, which show that after calibration, the average position errors of the industrial robot were decreased from 5.2944 mm, 3.1068 mm and 2.8433 mm to 0.2137 mm, 0.2385 mm and 0.2032 mm in x, y and z directions, respectively.
Keywords: kinematic calibration; parameter identification; industrial robot; genetic-tabu search algorithm; articulated arm coordinate measuring machine.