Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization

doi:10.1007/s12204-013-1376-3

上海交通大学学报（英文版） ›› 2013, Vol. 18 ›› Issue (2): 140-146.doi: 10.1007/s12204-013-1376-3

Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization

LI Xiang-bao* (李祥宝), JI Rui (季睿), YANG Yu-pu (杨煜普)

(Department of Automation, Shanghai Jiaotong University, Shanghai 200240, China)

出版日期:2013-04-30 发布日期:2013-05-10
通讯作者: LI Xiang-bao (李祥宝) E-mail:xiangbao.li@gmail.com

Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization

LI Xiang-bao* (李祥宝), JI Rui (季睿), YANG Yu-pu (杨煜普)

(Department of Automation, Shanghai Jiaotong University, Shanghai 200240, China)

Online:2013-04-30 Published:2013-05-10
Contact: LI Xiang-bao (李祥宝) E-mail:xiangbao.li@gmail.com

摘要/Abstract

摘要： Cryogenic ground support equipment (CGSE) is an important part of a famous particle physics experiment — AMS-02. In this paper a design method which optimizes PID parameters of CGSE control system via the particle swarm optimization (PSO) algorithm is presented. Firstly, an improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. Secondly, the way of finding PID coefficient will be studied by using this algorithm. Finally, the experimental results and practical works demonstrate that the CRPSO-PID controller achieves a good performance.

关键词: particle swarm optimization (PSO), PID controller, cryogenic ground support equipment (CGSE), cooperative random learning particle swarm optimization (CRPSO)

Abstract: Cryogenic ground support equipment (CGSE) is an important part of a famous particle physics experiment — AMS-02. In this paper a design method which optimizes PID parameters of CGSE control system via the particle swarm optimization (PSO) algorithm is presented. Firstly, an improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. Secondly, the way of finding PID coefficient will be studied by using this algorithm. Finally, the experimental results and practical works demonstrate that the CRPSO-PID controller achieves a good performance.

Key words: particle swarm optimization (PSO), PID controller, cryogenic ground support equipment (CGSE), cooperative random learning particle swarm optimization (CRPSO)

中图分类号:

TP 273

LI Xiang-bao* (李祥宝), JI Rui (季睿), YANG Yu-pu (杨煜普). Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization[J]. 上海交通大学学报（英文版）, 2013, 18(2): 140-146.

LI Xiang-bao* (李祥宝), JI Rui (季睿), YANG Yu-pu (杨煜普). Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization[J]. Journal of shanghai Jiaotong University (Science), 2013, 18(2): 140-146.

参考文献

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Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization

Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization

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