The Study Of Strategies In Fuzzy Control And Neural Network Control Based On Genetic Algorithms

The paper applies the Genetic Algorithms to optimizing the Fuzzy Control and Neural Network. It uses the global convergence to automatically optimize and design the parameter, structure and deduction principles, etc, in order to accomplish higher demands of the Intelligent Control. Fuzzy Control devices optimized by Genetic Algorithms have improved the control effect, stabilized the system and strengthened the swiftness and accuracy. Neural Network optimized by the Genetic Algorithms has broadened the searching space of the Neural Network, increased the efficiency of calculation and enlarged the automatic extent of constructing models. The simulating results indicate that the Intelligent Control system optimized by Genetic Algorithms has been highly improved in adaptability, timeliness and robustness.