On fuzzy sliding mode guidance based on self-adaptive genetic annealing algorithm

A new approach about design of controller (GL) for integrated self-adaptive genetic annealing algorithm (SGAA) and sliding mode control (SGAA-SMC) was proposed in this study. The main objective of this paper is to improve the non-minimum phase system performance by continuously updating the parameters of the sliding surface by SGAA. Firstly, Based on traditional fuzzy logic sliding mode control (FLSMC), the nonlinear variable region function was introduced, thus dynamic change of the fuzzy variable region can be realized. Next the self-adaptive simulated annealing genetic algorithm was employed to optimize the parameters of the sliding surface, which was designed by selecting adaptively the cross probability and mutation probability of the proposed algorithm and improved the stability and convergence of system. Finally, the simulation results were presented to show the validity of the proposed method.