微粒群算法在PID参数优化中的应用

The application of PSO in PID parameter optimization

微粒群算法是近年来兴起的一种智能优化算法,PID控制是当前工控领域运用最为广泛的一种控制方案,PID控制的效果与其三个参数息息相关,参数的设置与选取直接影响到控制系统的性能,本文基于MATLAB GUI设计出了可视化的仿真平台,利用PSO算法针对炼钢炉铁水温度控制系统PID控制器参数优化进行仿真研究,并和其它几种方案的控制效果进行比较,得出PSO算法应用于PID参数整定的可行性、有效性和优越性。

In recent years,particle swarm optimization is a kind of intelligent optimization algorithms,Currently PID control is the most widely used in industrial areas as a control program,The effect of PID control parameters are closely related to its three parameters, Parameter settings and selection has a direct impact on the performance of control systems,Based on MATLAB GUI the paper design a visual simulation platform,using PSO do simulation research of PID parameter optimization to hot metal for steelmaking furnace temperature control system,and compare the control effect to sever other scheme,Reach conclusion that The application of PSO in PID parameter optimization feasibility,effectiveness and superiority.