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

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