基于改进粒子群算法的双闭环直流电动机调速研究

Research on Double Closed-loop DC Speed-Regulation System Based on Improved Particle Swarm Optimization

针对现行PID控制器参数整定与优化的缺陷,通过将一种改进的粒子群优化算法(PSO)应用于双闭环直流调速系统,实现直流电动机调速及PID控制器参数在线优化。采用系统的阶跃响应等对改进PSO算法的优化结果进行对比分析,表明改进的PSO算法比传统工程设计法能获得更好的动态性能指标,以及更快的跟随性与鲁棒性,为PID参数优化提供了一个综合性能较好的实用方法。

For the defects of the parameter tuning and optimization of the PID controller, uses an improved Particle Swarm Optimization （IPSO） algorithm to apply on the dual closed-loop DC speed tuning system and adjust PID controller parameters online. The optimization result of adopting step response of the improved PSO algorithm is analyzed. It shows that using the improved PSO algorithm will obtain better dynamic performance, follow faster and more robustness than the traditional engineering design method. It provides a good performance of practical method for PID parameters optimization.