基于粒子群优化的混沌系统比例-积分-微分控制

Proportional-integral-derivative chaotic system control algorithm based on particle swarm optimization

基于比例-积分-微分(PID)控制算法的简单性和实用性,但对于复杂非线性系统控制时参数的难以确定问题,运用集群智能中的改进粒子群算法进行PID控制器的优化,并应用于若干混沌系统的控制.对H啨non混沌、Duffing混沌、六辊UC轧机混沌、Nagumo-sato神经元混沌、Chen氏混沌以及永磁同步电动机混沌的控制进行了仿真研究.研究结果表明:用PID进行混沌系统的输出反馈控制是有效的,从而拓宽了PID控制的应用范围;用简单方法控制复杂混沌系统是完全可能的,对混沌系统的控制具有较好的参考价值;粒子群优化算法对复杂混沌系统PID控制参数的优化不仅算法简单、易于编程,而且十分有效.

Proportional-integral-derivative（PID） control algorithm has the property of simplicity and practicability, but it is difficult to be tuned to control a complex nonlinear system. An advanced particle swarm optimization （PSO） was used to optimize the PID controller for controlling chaotic systems. Computer simulation of its application to several chaotic systems has been done. The controlled chaotic systems are the Hénon chaos, Duffing chaos, six-roll UC mill chaos, Nagumo-sato neuron chaos, Chen＇s chaos, and permanent magnet synchronous motor chaos. The chaos control simulation results show that： 1） The output feedback based PID control for chaotic systems is effective; 2） using PID to control complex chaotic systems is feasible; and 3） using PSO to optimize the PID parameters for chaos control is effective and simple in programming.