摘要
针对传统的PID参数整定控制性能指标不够理想的问题,提出一种基于改进粒子群算法的PID控制器参数控制方法,并将严重参数不确定性的直流伺服电机作为被控对象进行仿真研究.该算法是依据协同思想理论产生的,同时在进化过程中,引进因子p,增强全局的收索能力.Matlab仿真结果对比显示:改进的PSO-PID系统几乎无超调量,收敛时间短,能有效优化PID参数优化;直流伺服电机控制系统控制精度高,系统鲁棒性比较强,常规PSO-PID控制器的性能得到改善.
In order to solve the problem that the traditional PID parameter tuning control performance index is not ideal,a PID controller parameter control method based on improved particle swarm optimiza- tion algorithm is proposed,and the DC servo motor with severe parameter uncertainty is simulated as the controlled object. Based on collaborative theory,the algorithm enhances the overall collect ability with the introduction of factor p in the evolution process. The simulation results show that the improved PSO-PID system has almost no overshoot, the convergence time is short and the PID parameter optimization is effective. The DC servo motor control system has high control precision and strong system robustness, which improves the performance of the conventional PSO-PID controller.
出处
《徐州工程学院学报（自然科学版）》
CAS
2017年第3期78-81,共4页
Journal of Xuzhou Institute of Technology(Natural Sciences Edition)
基金
辽宁省自然科学基金项目(20170540119)
关键词
PID参数整定
粒子群算法
协同思想
因子
PID parameter setting
particle swarm algorithm
collaborative thought
factor
