GA-based New Optimization Method for Fuzzy Control Rules

The expert experience-based fuzzy control rules produce poor effects in some unknown dynamic environments.An improved decimal-coded adaptive genetic algorithm and automatically-generated global optimal control rules were presented.The steady-state propagation idea,and a dynamic mutation rate and a new adaptive mutation operator were introduced into this algorithm to improve the way of generating initial population,and to accelerate evolution progress and adjust the population diversity as well as to end prematurity phenomenon.The simulation results show that the newly-designed fuzzy controller can perform well.