Parameter Tuning of Fuzzy Sliding Mode Controller Using Particle Swarm Optimization

In this paper, an auto-tuning fuzzy sliding-mode controller design approach using particle swarm optimization (PSO) is proposed. This approach provides a simple way of designing a fuzzy sliding controller for nonlinear systems. Moreover, for this method the heuristic sliding factors are not needed to be known. Therefore, the proposed method eliminates the trial-and-error process for finding the appropriate sliding factors and fuzzy parameters. The superiority of the proposed auto-tuning technique is that there is no need for the partial derivative with respect to the parameter for parameter tuning. All parameters of fuzzy controller are auto-tuned by PSO in the proposed approach. This paper proposes and describes an effective utilization of PSO to design and tune fuzzy sliding mode controller for highly nonlinear systems. The simulation results for four highly nonlinear chaotic systems are presented to demonstrate the effectiveness and robustness of the proposed method. Simulation results show the high performances of the proposed method for stabilizing the unstable periodic orbits of chaotic systems.