Dezhi Xu

A Novel Model-Free Adaptive Control Design for Multivariable Industrial Processes

In this paper, a multiple adaptive observer-based strategy is proposed for the control of multi-input multi-output nonlinear processes using input/output (I/O) data. In the strategy, the pseudopartial-derivative parameter matrix of compact form dynamic linearization is estimated by a multiple adaptive observer, which is used to dynamically linearize a nonlinear system. Then, the proposed data-driven model-free-adaptive-control algorithm is only based on the online identified multiobserver models derived from the I/O data of the controlled plants, and Lyapunov-based stability analysis is used to ensure that all signals of the close-loop control system are bounded. A numerical example and a Wood/Berry distillation column example are provided to show that the proposed control algorithm has a very reliable tracking ability and a satisfactory robustness to disturbances and process dynamics variations.

Adaptive observer based data-driven control for nonlinear discrete-time processes

In this paper, two adaptive observer-based strategies are proposed for control of nonlinear processes using input/output (I/O) data. In the two strategies, pseudo-partial derivative (PPD) parameter of compact form dynamic linearization and PPD vector of partial form dynamic linearization are all estimated by the adaptive observer, which are used to dynamically linearize a nonlinear system. The two proposed control algorithms are only based on the PPD parameter estimation derived online from the I/O data of the controlled system, and Lyapunov-based stability analysis is used to prove all signals of close-loop control system are bounded. A numerical example, a steam-water heat exchanger example and an experimental test show that the proposed control algorithm has a very reliable tracking ability and a satisfactory robustness to disturbances and process dynamics variations.

Robust NSV Fault-Tolerant Control System Design Against Actuator Faults and Control Surface Damage Under Actuator Dynamics

In this paper, a decentralized fault-tolerant control (FTC) system is proposed for near-space vehicle (NSV) attitude dynamics. First, NSV reentry attitude dynamic models with an uncertainty, actuator failure models, and a control surface damage model are described. Next, a new local fault identification algorithm is proposed to iden tify different types of actuator faults, which is based on multiobserver techniques. The local fault identification is constituted by a fault detection observer, fault parameter identification observers, and a decision-making mechanism. Then, a global adaptive sliding-mode observer is used to design the command filter backstepping fault- tolerant controller. Our focus is on the accommodation for actuator faults, control surface damage, uncertainties, and the resulting disturbances of the NSV. Finally, simulation results are given to demonstrate the effectiveness and poten tial of the proposed FTC scheme.

A Novel Adaptive Neural Network Constrained Control for a Multi-Area Interconnected Power System With Hybrid Energy Storage

This paper concentrates on the problem of control of a hybrid energy storage system (HESS) for an improved and optimized operation of load-frequency control applications. The HESS consists of a supercapacitor serving as the main power source and a fuel cell serving as the auxiliary power source. First, a Hammerstein-type neural network is proposed to identify the HESS, which formulates the Hammerstein model with a nonlinear static gain in cascade with a linear dynamic block. It provides the model information for the controller to achieve the adaptive performance. Second, a feedforward neural network based on a back-propagation training algorithm is designed to formulate the proportional-integral-derivative (PID)-type neural network, which is used for the adaptive control of the HESS. Meanwhile, a dynamic antiwindup signal is designed to solve the operational constraint of the HESS. Then, an appropriate power reference signal for the HESS can be generated. Third, the stability and the convergence of the whole system are proved based on the Lyapunov stability theory. Finally, simulation experiments are followed through on a four-area interconnected power system to demonstrate the effectiveness of the proposed control scheme.

Model-Free Adaptive Discrete-Time Integral Sliding-Mode-Constrained-Control for Autonomous 4WMV Parking Systems

In this paper, a new model-free adaptive integral sliding-mode-constrained control scheme is presented for autonomous four-wheeled mobile vehicle (4WMV) parking systems. The proposed control strategy includes: 1) online identification for the object model based on a data-driven technique is presented for 4WMV and 2) an integral sliding-mode controller with control input constraints and stability analysis is provided. For online data-driven model identification, a compact-form dynamic linearization-based observer formulation is constructed for 4WMV. For integral sliding-mode controller design, a dynamic antiwindup compensator is introduced to solve integral saturation and actuator saturation problems in the autonomous 4WMV parking system. The designed control scheme only utilizes the body angle and steering angle of the vehicle under the condition that the precise mechanism model of the autonomous 4WMV parking system is not available to us. Finally, simulation comparisons between the model-free adaptive integral sliding-mode-constrained control scheme, PID control, and model-free adaptive control algorithms with coordinate compensation are given for two different vehicles. The simulation results show that a better control performance is achieved with the proposed new sliding-mode controller than the traditional control method when actuator or control input saturation exists in the autonomous 4WMV parking system.

Nonlinear Control of Back-to-Back VSC-HVDC System via Command-Filter Backstepping

This paper proposed a command-filtered backstepping controller to improve the dynamic performance of back-to-back voltage-source-converter high voltage direct current (BTB VSC-HVDC). First, the principle and model of BTB VSC-HVDC in abc and d-q frame are described. Then, backstepping method is applied to design a controller to maintain the voltage balance and realize coordinated control of active and reactive power. Meanwhile, command filter is introduced to deal with the problem of input saturation and explosion of complexity in conventional backstepping, and a filter compensation signal is designed to diminish the adverse effects caused by the command filter. Next, the stability and convergence of the whole system are proved via the Lyapunov theorem of asymptotic stability. Finally, simulation results are given to demonstrate that proposed controller has a better dynamic performance and stronger robustness compared to the traditional PID algorithm, which also proves the effectiveness and possibility of the designed controller.

Adaptive Command-Filtered Backstepping Control for Linear Induction Motor via Projection Algorithm

A theoretical framework of the position control for linear induction motors (LIM) has been proposed. First, indirect field-oriented control of LIM is described. Then, the backstepping approach is used to ensure the convergence and robustness of the proposed control scheme against the external time-varying disturbances via Lyapunov stability theory. At the same time, in order to solve the differential expansion and the control saturation problems in the traditional backstepping, command filter is designed in the control and compensating signals are presented to eliminate the influence of the errors caused by command filters. Next, unknown total mass of the mover, viscous friction, and load disturbances are estimated by the projection-based adaptive law which bounds the estimated function and simultaneously guarantees the robustness of the proposed controller against the parameter uncertainties. Finally, simulation results are given to illustrate the validity and potential of the designed control scheme.

Active fault tolerant control design approach for the flexible spacecraft with sensor faults

Abstract In this paper, the problem of active fault tolerant control (FTC) is studied for a class of flexible spacecraft attitude systems with Lipschitz nonlinearity and sensor fault. Firstly, a functional observer is designed for the attitude systems of flexible spacecraft in order to detect the time of unknown sensor fault occurred. Next, the sensor fault estimation is performed by filtering the output estimation error, as usually done in the residual generation framework. Then, a dynamic output feedback-based FTC approach is proposed to the flexible spacecraft in sensor faulty case, it not only attenuates flexible appendage disturbance with a given level γ, but also tolerates the effect of unknown sensor fault. Finally, the effectiveness of the proposed FTC method is demonstrated in the attitude systems of flexible spacecraft subject to a time-varying sensor fault.

Adaptive command-filtered fuzzy backstepping control for linear induction motor with unknown end effect

Abstract In this paper, the problem of the speed control is considered for linear induction motor with the end effects, uncertain system parameters, and external load disturbance. Firstly, the proposed controller is based on backstepping method, and the adaptive laws are designed.The fuzzy logic modeling approach is used to deal with the unknown nonlinear functions and uncertain parameters. Secondly, a constrained command filter is employed to overcome the problem of differential expansion and controller saturation in the backstepping method, and a filter’s compensating signal is used to mitigate the error caused by the constrained command filter. Thirdly, the projection operator introduced in the adaptive laws guarantees boundedness of the estimated functions and robustness of the designed controller in the presence of time-varying disturbances and uncertainties. Thus, the proposed control controller can ensure that all response signals in the closed-loop system are bounded. Finally, the effectiveness of the proposed controller is verified by simulation and comparison with command-filtered backstepping controller.

Improved Model-Free Adaptive Sliding-Mode-Constrained Control for Linear Induction Motor considering End Effects

As a kind of special motors, linear induction motors (LIM) have been an important research field for researchers. However, it gives a great velocity control challenge due to the complex nonlinearity, high coupling, and unique end effects. In this article, an improved model-free adaptive sliding-mode-constrained control method is proposed to deal with this problem dispensing with internal parameters of the LIM. Firstly, an improved compact form dynamic linearization (CFDL) technique is used to simplify the LIM plant. Besides, an antiwindup compensator is applied to handle the problem of the actuator under saturations in case during the controller design. Furthermore, the stability of the closed system is proved by Lyapunov stability method theoretically. Finally, simulation results are given to demonstrate that the proposed controller has excellent dynamic performance and stronger robustness compared with traditional PID controller.