Study on the sliding mode fault tolerant predictive control based on multi agent particle swarm optimization

Abstract

For a class of uncertain discrete-time systems with time varying delay, the problem of robust fault-tolerant control for such systems is studied by combining the design of sliding mode control (SMC) and model predictive control (MPC). A sliding mode fault tolerant predictive control based on multi agent particle swarm optimization (PSO) is presented, and the design, analysis and proof of the scheme are given in detail. Firstly, the sliding mode prediction model of the system is designed by assigning poles of the output error of the system. The model has time varying characteristics, and it can improve the motion quality of the system while ensuring the sliding mode is stable. Secondly, a new discrete reference trajectory considering time-delay systems subjected simultaneously to parameter perturbations and disturbances is proposed, which not only can ensure that the state of the system has good robustness and fast convergence in the process of approaching sliding mode surface, but also can inhibit chattering phenomenon. Thirdly, the multi agent PSO improves the receding-horizon optimization, which can quickly and accurately solve the control laws satisfying the input constraints, and can effectively avoid falling into local extrema problem of the traditional PSO. Finally, the theoretical proof of robust stability of the proposed control scheme is given. Experimental results of quad-rotor helicopter semi physical simulation platform show that the state of uncertain discrete-time systems with time varying delay is stable under the action of the proposed control scheme in this paper. The advantages of fast response, less overshoot and small control chattering prove the feasibility and effectiveness of the proposed control scheme.