In view of the classic particle swarm algorithm in PID controller parameter setting method of its effect is often poor, this paper puts forward an improved particle swarm algorithm optimization design of the PID controller parameter setting, on the basis of the particle swarm to join the crossover operator of genetic algorithm, and the particle swarm of inertia weight factor into a dynamic parameter, The applied PID controller improves the adaptive tuning of parameters, and the rapidity and stability are better than those of the classical PSO PID controller. With the help of Matlab to simulate the response curve of the system, according to the comparison of the system performance index improvement.
董如意, 唐玉玉, 桑可可. 基于改进粒子群算法的PID控制器参数整定优化
[J]. 吉林化工学院学报, 2022, 39(7): 18-21.
Dong ruyi, Tang yuyu, Sang keke. Optimization Design of PID Controller based on Particle Swarm Optimization Algorithm
. Journal of Jilin Institute of Chemical Technology, 2022, 39(7): 18-21.