Optimal Design of T-S Fuzzy Controller Based on Improved Genetic Algorithm

To solving the problem that there had been too many undetermined parameters in the fuzzy control rules, it presented a simplified Takagi-Sugno, namely T-S, fuzzy reasoning method. It reduced the parameters of the IF-THEN rules greatly. In addition this paper also improved the genetic algorithm on the analysis of the prior genetic algorithm, by which the global optimal parameters of the controller can be found easily and quickly thus the control rules can be amended and perfected. The simulation results show that the improved genetic algorithm can find the optimal parameters at a high speed and the optimized T-S fuzzy controller can obtain an excellent control performance.