Sliding mode control based on particle swarm optimization and support vector machine

In this paper, a new method of sliding mode control (SMC) is proposed for a class of discrete-time system based on particle swarm optimization (PSO) and support vector machine (SVM). Parameters, which were limited by determining previously in the conventional reaching law, are adjusted by PSO and SVM on line. The tracking speed of the control system is accelerated according to this method. The disadvantages of large calculation and low precision of SVM are overcome by the method of combination to the PSO. And quality of control system is improved and the system chattering is weakened through the method. Simulation results show the effectiveness of it.