Optimal Study Of Fuzzy Controller Based On Genetic Algorithms

Fuzzy controller (FC) is a kind of intelligent controller, which imitates human thoughts, uses the information of our language, so fuzzy controller comprehended easily, design simply, maintenance conveniently. Because of fuzzy controller based on control rules including fuzzy information, stability and robusticity of control systems, which consist of fuzzy controller, are better than those of general controller. During improving system characteristics, fuzzy control systems may modify system characteristic by changing control rules, membership function, reasoning methods and decision-making methods, rather adjusting parameters like general control systems. Genetic algorithm (GA) is a kind of convergent algorithm with self-adaptation, elicitation, colony, probability, and iteration on whole range. Optimizing FC using GA's good search characteristics may obtain better control results. genetic algorithms is applied to optimize membership functions and control rules, and the simulation results of before and after optimization are compared. The simulation results indicate that this control strategy has very good effects.