摘要
PID参数优化一直是自动控制领域研究的重要问题,PID的控制效果取决于比例、积分和微分三个参数取值。传统的PID参数多采用试验加试凑的方式由人工进行优化,难以满足控制的实时要求。为了解决控制参数优化选择问题,改善系统性能,提出一种基于粒子群算法的PID参数优化策略。通过建立粒子群优化的PID控制器参数模型,在控制过程中将PID参数(比例、积分、微分)作为粒子群中的粒子,采用控制误差绝对值时间积分函数作为优化目标,在控制过程中动态调整PID的三个控制参数,从而进行PID控制参数的实时优化,最后将优化方案应用于中央空调温度控制系统。仿真应用研究表明,PID参数优化策略具有很强的灵活性、适应性和鲁棒性,进而验证了优化方案的可行性和有效性。
The setting and optimization of PID parameters are always the important stady topics in the automatic control field.The control effect depends on PID controller,integral and proportion of differential three parameters,both mutual coordination and interdependent relationship.Original optimization method is a time-consuming method and can not get satisfied control effect.In order to solve this problem,article Swarm Optimization method is applied to PID controller.Through the establishment of particle swarm algorithm of PID controller parameters optimization model,in the proportion of PID control process devastates,integral,differential parameters as particle swarm of particles,Find the PID parameters optimizing design is targeted.It can adjust three control parameters in control process and thus sets PID parameters on line.Simulation results indicate that the PID control,PSO controller has stronger adaptability and better results.
出处
《计算机仿真》
CSCD
北大核心
2010年第10期191-193,222,共4页
Computer Simulation
关键词
粒子群算法
比例积分微控制器
参数整定
仿真
Particle swarm optimization(PSO)
PID controller
Parameter setting
Simulation