Research on tuning PID parameters based on improved particle swarm optimization algorithms

doi:10.3778/j.issn.1002-8331.2009.25.074

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (25): 240-241.DOI: 10.3778/j.issn.1002-8331.2009.25.074

• 工程与应用 • Previous Articles Next Articles

Research on tuning PID parameters based on improved particle swarm optimization algorithms

LI Li-li^1,2，WANG Qiang³，WANG Xiao-xiao¹

1.College of Physics and Electronic Information Engineering，Guangxi Normal University，Guilin，Guangxi 541004，China
2.Department of Physics and Electronic Information，Hezhou University，Hezhou，Guangxi 542800，China
3.College of Computer and Information Engineering，Guangxi Normal University，Guilin，Guangxi 541004，China

Received:2008-07-31 Revised:2008-10-06 Online:2009-09-01 Published:2009-09-01
Contact: LI Li-li

改进粒子群优化算法在PID参数整定中的研究

李立礼^1,2，王强³，王晓霄¹

1.广西师范大学物理与电子工程学院，广西桂林 541004
2.广西贺州学院物理与电子信息系，广西贺州 542800
3.广西师范大学计算机与信息工程学院，广西桂林 541004

通讯作者: 李立礼

Abstract

Abstract: In order to avoid the premature convergence of the Particle Swarm Optimization（PSO） algorithm，a modified PSO algorithm is proposed.Aggregate degree of particle swarm and mutation idea are introduced to upgrade the performance of the new algorithm.As an example，the improved algorithm is used for tuning PID controller parameters and the experiment result has proved its efficiency.

Key words: particle swarm optimization, mutation, Proportion Integration Differentiation（PID）

摘要： 针对粒子群优化算法（PSO）容易出现早熟收敛的问题，提出一种改进的粒子群优化算法（IMPSO）。该算法通过引入粒子群聚合度和变异的思想，能很好避免早熟，提高粒子全局搜索能力。将此改进的粒子群优化算法用于PID控制器的参数整定，具有操作简单，寻优快速等优点。

关键词: 粒子群优化算法, 变异, 比例、积分、微分（PID）

LI Li-li^1,2，WANG Qiang³，WANG Xiao-xiao¹. Research on tuning PID parameters based on improved particle swarm optimization algorithms[J]. Computer Engineering and Applications, 2009, 45(25): 240-241.

李立礼^1,2，王强³，王晓霄¹. 改进粒子群优化算法在PID参数整定中的研究[J]. 计算机工程与应用, 2009, 45(25): 240-241.

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Research on tuning PID parameters based on improved particle swarm optimization algorithms

改进粒子群优化算法在PID参数整定中的研究

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