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。
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 t, 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.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第17期4-7,共4页
Computer Engineering and Applications
基金
国家高技术研究发展计划(863) (the National High- Tech Research and Development Plan of China under Grant No.2003AA132050)
关键词
蚁群算法
PID
信息素
遗传算法
ZN法
ant colony algorithm
PID
pheromone
genetic algorithm
ZN method
