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利用改进粒子群算法整定PID参数
引用本文:肖理庆,邵晓根,石天明,张亮.利用改进粒子群算法整定PID参数[J].计算机应用,2010,30(6):1547-1549.
作者姓名:肖理庆  邵晓根  石天明  张亮
作者单位:1. 徐州工程学院2.
基金项目:江苏省高校自然科学研究项目(09KJD120005);;徐州工程学院校科研基金资助项目(XKY2007233)
摘    要:PID控制器的性能取决于其控制参数的组合,针对其参数的整定与优化问题,提出了一种改进的粒子群算法,该算法将区间算法与轮盘赌选择引入种群微粒位置的初始化操作。仿真实验表明,新算法能有效克服早熟收敛现象,降低随机性初始种群的影响,提高算法收敛精度。

关 键 词:PID控制器  粒子群算法  区间算法  轮盘赌选择  早熟收敛  
收稿时间:2009-12-15
修稿时间:2010-03-07

Tuning PID parameters with improved particle swarm optimization
XIAO Li-qing,SHAO Xiao-gen,SHI Tian-ming,ZHANG Liang.Tuning PID parameters with improved particle swarm optimization[J].journal of Computer Applications,2010,30(6):1547-1549.
Authors:XIAO Li-qing  SHAO Xiao-gen  SHI Tian-ming  ZHANG Liang
Affiliation:1.College of Information and Electrical Engineering/a>;Xuzhou Institute of Technology/a>;Xuzhou Jiangxu 221008/a>;China/a>;2.College of Information and Control Engineering/a>;China University of Petroleum/a>;Dongying Shandong 257061/a>;China
Abstract:The performance of PID controller depends on the combination of the control parameters.An improved particle swarm optimization was proposed for tuning and optimizing PID parameters,by applying interval algorithm and roulette wheel selection to the initialization of particle location.The simulation and experimental results show that,the proposed algorithm can overcome premature phenomena,reduce the influence of random initial population,and improve the convergence precision,which means a good application pro...
Keywords:PID controller                                                                                                                        particle swarm optimization                                                                                                                        interval algorithm                                                                                                                        roulette wheel selection                                                                                                                        premature convergence
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