Optimization of stable rules for fuzzy controller using genetic algorithms
P.T. Chan, K.M. Tsang, Amir Besharati Rad · PolyU Institutional Research Archive (Hong Kong Polytechnic University) · 2003
This article proposes a stable fuzzy system (FS) optimized by genetic algorithm (GA). The FS uses GA to search the optimal fuzzy rules. As GA has some random properties, which may cause unstability, a supervisory controller (designed by Lyapunov stability analysis) is used to ensure the stability of the system. The algorithm is designed to combine a priori knowledge of the system and mechanisms of GA to improve the convergence of the optimization. The efficiency of the approach is verified by computer simulation.