Open AccessSelf-Tuning of PID Parameters Based on Adaptive Genetic Algorithm
Author(s) -
Jimin Zhao,
Miao Xi
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/782/4/042028
Subject(s) - pid controller , crossover , overshoot (microwave communication) , genetic algorithm , control theory (sociology) , computer science , selection (genetic algorithm) , algorithm , control engineering , engineering , artificial intelligence , machine learning , control (management) , temperature control , telecommunications
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.