PSO&GA

代码说明：

  本文件对PID参数kp,ki,kd进行寻优，以ITAE作为指标函数。 PSO 文件中有详细的参数设置和寻优过程 GA寻优与PSO寻优作为对比出现 figure1展示了随着迭代次数的变化，适应度函数的收敛情况 figure2展示了kp,ki,kd的迭代情况 ht 文件是用来画图的 问题解决思路.pdf 简要介绍了粒子群算法寻优的过程(In this document, the PID parameters KP, Ki, KD are optimized, and ITAE is used as the index function. PSO file has detailed parameter settings and optimization process GA optimization and PSO optimization as a contrast appear Figure1 shows the convergence of fitness function as the number of iterations changes Figure2 shows the iterations of KP, Ki, and KD The HT file is used for drawing The problem solving idea.Pdf briefly introduces the process of particle swarm optimization)

文件列表：

chapter14\GA_run.m
chapter14\PSO.m
chapter14\PSO_PID.m
chapter14\问题解决思路.pdf
chapter14\ht.m
chapter14\kp.fig
chapter14\ki.fig
chapter14\kd.fig
chapter14\清单.txt
chapter14
PSO&GA\GA_run.m
PSO&GA\PID_Model.mdl
PSO&GA\PSO.m
PSO&GA\PSO_PID.m
PSO&GA\问题解决思路.pdf
PSO&GA\figure2.fig
PSO&GA\figure1.fig
PSO&GA\ht.m
PSO&GA\kp.fig
PSO&GA\ki.fig
PSO&GA\kd.fig
PSO&GA\清单.txt
PSO&GA