Model reference adaptive sliding mode control for switched linear systems

Author(s):  
Shen Zhang ◽  
Qing Wang ◽  
Jinjin Liang ◽  
Chaoyang Dong
Author(s):  
Junfeng Jiang ◽  
Xiaojun Zhou ◽  
Wei Zhao ◽  
Wei Li

A model reference adaptive sliding mode control for the position control of the permanent magnet synchronous motor is developed in this article. First of all, a fast sliding surface is designed to achieve faster convergence than the ordinary sliding mode control. Then, the adaptive laws are developed to make the control parameters, especially the switching gain, updated online. Therefore, the chattering can be reduced effectively and the disturbance can be rejected well. Finally, a reference model which produces an exponential decay curve is applied for the position error to follow. Thus, not only fast error convergence can be guaranteed, but also the dynamic process of the system response can be controlled easily by modifying the decay rate of the reference model. The proposed model reference adaptive sliding mode control scheme combines the advantages of the sliding mode control and the model reference adaptive control. Simulation and experimental results reveal that faster and more accurate performance with smoother control signal and better robustness is obtained compared with other methods. Also, the model reference adaptive sliding mode control method can maintain good performance when the system inertia or the position reference varies in a wide range.


Author(s):  
Hongliang Xiao ◽  
Huacong Li ◽  
Jia Li ◽  
Jiangfeng Fu ◽  
Kai Peng

As to solve the problem of multivariable output tracking control of variable cycle engine under system uncertainties and external disturbances, an augmented model reference adaptive sliding mode control method based on LQR method was developed. Firstly, the model is augmented and the reference state is provided to the controller by designing the reference model using the optimal LQR method. Then, based on the state tracking sliding mode control method, the adaptive law is derived based on the strict stability condition of Lyapunov function to estimate the upper bound of the system perturbation matrix and the upper bound of the external disturbances. Finally, the controller achieves the asymptotic zero tracking error of the system under the conditions of uncertainty and external disturbance. The simulation results showed that the LQR-based augmented model reference adaptive sliding mode control method can solve the problem that the traditional sliding mode control method needs to specify the reference state in advance and improve the control performance of the variable cycle engine control with system uncertainties and external disturbance. The tracking of the control command is effectively achieved and the steady-state and dynamic performance are improved. The steady-state control errors under different conditions are less than 0.1%, the system overshoot is less than 0.5%, and the adjustment time is less than 1s, which conformed to the requirements of the aero engine control system technology.


2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Hongliang Xiao ◽  
Huacong Li ◽  
Kai Peng ◽  
Jia Li

Abstract In this paper, a model reference adaptive sliding mode control method is proposed for a variable cycle engine (VCE) which is a MIMO system with uncertainties and external disturbances. The reference model is designed based on optimal LQR method to provide ideal reference states. An adaptive sliding mode controller (ASMC) is designed for model reference adaptive control structure, which the adaptive law is derived based on Lyapunov function to estimate the unknown upper bound of uncertainties and external disturbances. Simulation results for VCE demonstrate the performance and fidelity of the proposed method.


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