Tuning parameters of PID controller based on fuzzy logic controlled genetic algorithms

To solve the problem of tuning parameters of PID controller using the conventional genetic algorithm, an improved genetic algorithm based on fuzzy inference is proposed. On the basis of generalizing heuristic knowledge about crossover and mutation operations, a fuzzy controller is designed to adaptively adjust the crossover rate and mutation rate. The fuzzy logic controlled genetic algorithm (FCGA) improves global optimization ability of the standard genetic algorithm. We apply it to adaptive PID controller. The comparison between the FCGA and the SGA is performed, which demonstrates that the FCGA has much better capability of parameters optimization and convergent speed, and it can also fulfill the requirement of real-time control.