计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (17): 4-7.

• 博士论坛 • 上一篇    下一篇

基于蚁群算法的PID控制参数优化

尹宏鹏,柴 毅   

  1. 重庆大学 自动化学院,重庆 400044
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-06-11 发布日期:2007-06-11
  • 通讯作者: 尹宏鹏

Parameters optimization design of PID controller based on ant colony algorithms

YIN Hong-peng,CHAI Yi   

  1. College of Automation,Chongqing University,Chongqing 400044,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-06-11 Published:2007-06-11
  • Contact: YIN Hong-peng

摘要: 蚁群算法是近几年优化领域中新出现的一种仿生进化算法,该算法采用的分布式并行计算机制特别适用于组合优化问题(COP)的求解。在简要介绍蚁群算法的基础上,针对PID控制参数整定问题提出了一种基于蚁群算法的PID参数优化策略,并给出了该算法的具体实现步骤。仿真试验结果表明同传统的Ziegler-Nichols(ZN)法、遗传算法优化整定的结果进行比较,系统单位阶跃响应的超调量σ分别减少了51.5%和22%和调整时间ts分别减少了61.4%和67.5%,动态和稳态性能进一步改善,进而验证了该方法的可行性和有效性。

关键词: 蚁群算法, PID, 信息素, 遗传算法, ZN法

Abstract: Ant colony algorithm is a new emerging bionic evolutionary algorithm,which employs distributed parallel computer system and is particularly applicable to the solution of Combinatorial Optimization Problems(COP).This paper,giving a brief introduction to the ant colony algorithm,presents a PID algorithm based ant colony algorithm optimization strategy and specific steps to realize it.Simulation results show that the unit step response system reduces the overshoot by 51.5% and 22% respectively and settling time ts decrease to 61.4% and 67.5% respectively,compared to the traditional Ziegler-Nichols(ZN) method and genetic algorithm.The further improvement of the dynamic and static performance proves the feasibility and effectiveness of this method.

Key words: ant colony algorithm, PID, pheromone, genetic algorithm, ZN method