Self-Tuning of PID Parameters Based on Adaptive Genetic Algorithm

Abstract

Aiming at the problems existing in the PID parameter tuning of traditional genetic algorithms, a method of applying adaptive genetic algorithms to parameter tuning was proposed. It takes system overshoot and dynamic performance indicators as the objective function, optimizes the crossover and selection probability in the genetic algorithm, reduces the probability of the system entering a local optimum, and makes the system converge faster. Comparing the traditional manual tuning PID and the genetic algorithm (GA) PID controller with the adaptive genetic algorithm (AGA) PID controller, it is concluded that the use of adaptive genetic algorithm can improve the performance indicators of the system.