[1]王海稳,张井岗,曲俊海.基于PSO算法的目标值前馈型二自由度PID控制器的优化设计[J].智能系统学报,2006,1(02):58-61.
 WANG Hai-wen,ZHANG Jing-gang,QU Jun-hai.Optimal design for two degreeoffreedom PID controller based on PSO algorithm[J].CAAI Transactions on Intelligent Systems,2006,1(02):58-61.
点击复制

基于PSO算法的目标值前馈型二自由度PID控制器的优化设计(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第1卷
期数:
2006年02期
页码:
58-61
栏目:
学术论文—智能系统
出版日期:
2006-10-25

文章信息/Info

Title:
Optimal design for two degreeoffreedom PID controller based on PSO algorithm
文章编号:
1673-4785(2006)02-0058-04
作者:
王海稳1 张井岗1 曲俊海2
1.太原科技大学电子信息工程学院,山西太原030024;
2.中国兵器工业集团第207研究所,山西太原030006
Author(s):
WANG Hai-wen1ZHANG Jing-gang1QU Jun-hai2
1.College of Electronic and Information Engineering, Taiyuan Univers ity of Science and Technology, Taiyuan 030024, China;
2. The 207 Research Instit ute, China North Industri es Group Corporation, Taiyuan 030006, China
关键词:
二自由度控制PID控制微粒群优化参数优化
Keywords:
twodegreeoffreedom control PID control partic le swarm optimization parameters optimization
分类号:
TP273
文献标志码:
A
摘要:
微粒群优化算法是一种全局优化技术,算法简单、容易实现.其通过微粒间的相互作用发现复杂搜索空间中的最优区域.提出了将微粒群优化算法用于二自由度PID控制器参数的寻优设计中,并以工业过程中常见的对象为模型,进行了Matlab仿真试验,仿真结果表明系统同时具有了最优的目标值跟踪特性和干扰抑制特性,证明了PSO算法的有效性
Abstract:
Particle swarm optimization (PSO) algorithm is a random global optimization tec hnology. The algorithm is simple and easy to be implemented. Through interaction between particles, the algorithm canfind the optimal area in complicated search in g space. A method is presented, for optimizing twodegreeoffreedom PID con troller paramete r by using PSO algorithm and then optimization algorithm is tested by simulation experiment in the common industrial model based on MATLAB. The si mulation results show that the system is simultaneously both the characteristics of command tracking and disturbance rejection. The simulation verifies the e ffectiveness of the PSO algorithm.

参考文献/References:

[1] 张井岗,李临生,陈志梅. 二自由度PID调节器的内模整定方法[J].仪器仪表学报,2002,23(1),23-28. ZHANG Jinggang, LI Linsheng, CHEN Zhimei. IMC tuning of twodegreeoffreedo m PID regulator[J]. Chinese Journal of Scientific Instrument, 2002, 23(1), 28- 30.
[2]徐洪泽,徐漫涛,张恩福. 一种改进的基于用于二自由度PID调节器设计[J] .系统仿真学报,1999, 11(2),59-64. XU Hongze,XU Mantao,Fuen Zhang. Twodegreeoffreedom PID regulator design using an improved genetic algorithm[J]. Journal of System Simulation, 1999,11 (2),59-64. 
[3]王  强,麻  亮. 基于改进混合遗传算法的二自由度PID控制器设计与应用[J ].控制与决策,2001,16(2):195-198. WANG Qiang,MA Liang. Design for 2DOF PID controller based on hybrid geneti c algorithm and its application[J]. Control and Decision, 2001, 16(2):195-198. 
[4]霍海波,张井岗,王卫红. 一种基于自适应基于算法的二自由度PID调节器设计[J].太原重型机械学院学报,2005,26(1), 42-45. HUO Haibo, ZHANG Jinggang, WANG Weihong. Design for 2DOF PID regulator based o n adaptive genetic algorithm[J]. Jounal of Taiyuan Heavy Machinery Institute, 2005, 26(1), 42-45.
[5]KUNG Y S,LIAW C M,OUYANG M S. Adaptive speed control for indu ctionmotor drives using neural networks[J].IEEE Trans Ind Electron. 1995,42(1 ):25-32.
[6]邱公伟,林瑞全. 参数自整定二自由度PID全神经元实现的仿真研究[J].系统仿真学报,2003, 14(10),1293-1295.
QIU Gongwei, LIN Ruiquan. Full neuron realization of parameters autoadjusti ng twodegreeoffreedom PID[J]. Journal of System Simulation, 2003, 14(10) ,1293-1295. 
[7]邱公伟. 神经元滤波型2自由度PID控制器研究[J].信息与控制,2003, 3 1(6),557-560.
QIU Gongwei. Study of single neuron filtering twodegreeoffreedom PID contr oller[J]. Information and Control, 2003, 31(6), 557-560.
[8]LIAW C M, CHENG. S Y. Fuzzy twodegreesoffreedom speed control ler for motor driver[J].IEEE Trans Ind Electron,1995,42(2):209-216.
[9]LIAW C M, LIN F J. Position control with fuzzy adaptation for induct ion servomotor drive[J].IEE Proc Electr Power Appl,1995, 142(6):397-404. 
[10]谢晓峰,张文俊,杨之廉. 微利群算法综述[J].控制与决策,2003,18(2), 129-134.
 XIE Xiaofeng, ZHANG Wenjunn, YANG Zhilian. Overview of Particle Swarm Optim ization[J]. Control and Decision, 2003,18(2), 129-134.
[11]ARAKI M , HIDEFUMI T. Twodegreeoffreedom PID controllers[J] . International Journal of Control, Automation, and Systems, 2003,1(4):401-410. 
[12]TAGUCHI H, DOI M, ARAKI M. Optimal parameters of twodegreeoff reedom PID control systems[J]. Trans SICE, 1987,23(5): 889-895.

相似文献/References:

[1]吴晓威,张井岗,赵志诚.基于灰色预测的自适应内模PID双重控制器设计[J].智能系统学报,2008,3(01):71.
 WU Xiao-wei,ZHANG Jing-gang,ZHAO Zhi-cheng.Design of a dual controller with an adaptive internal model and PID in conjunction with grey prediction[J].CAAI Transactions on Intelligent Systems,2008,3(02):71.
[2]张 波,刘冀伟,崔朝辉,等.双目视觉模型移动目标跟踪系统[J].智能系统学报,2010,5(05):400.[doi:10.3969/j.issn.1673-4785.2010.05.004]
 ZHANG Bo,LIU Ji-wei,CUI Zhao-hui,et al.Design and implementation of a binocular vision moving target tracking system[J].CAAI Transactions on Intelligent Systems,2010,5(02):400.[doi:10.3969/j.issn.1673-4785.2010.05.004]
[3]张文辉,周启航,齐乃明.模糊CMAC的柔性空间机器人轨迹跟踪自学习控制[J].智能系统学报,2012,7(05):457.
 ZHANG Wenhui,ZHOU Qihang,QI Naiming.Trajectory tracking selfstudy control for flexible space manipulators with fuzzy CMAC[J].CAAI Transactions on Intelligent Systems,2012,7(02):457.
[4]林峰,杨忠程,冯英,等.利用场景光照识别优化的双目活体检测方法[J].智能系统学报,2020,15(1):160.[doi:10.11992/tis.201912026]
 LIN Feng,YANG Zhongcheng,FENG Ying,et al.Binocular camera based face liveness detection with optimized scene illumination recognition[J].CAAI Transactions on Intelligent Systems,2020,15(02):160.[doi:10.11992/tis.201912026]

备注/Memo

备注/Memo:
收稿日期:2006-02-28.
基金项目:太原科技大学青年基金资助项目(2006103).
作者简介:
王海稳,女,1978年生,硕士,2001年毕业于太原重型机械学院,主要研究方向为智能控制和二自由度控制.
E-mail:whw78@sohu.com
张井岗,男,1965年生,教授,主要研究方向为鲁棒控制和智能控制及其应用,主持和完成国家九五攻关项目、山西省自然科学基金项目、山西省青年科学基金项目等研究课题,发表学术论文60多篇,其中18篇分别被EI、ISTP收录
曲俊海,男,1979年生,2001年毕业于太原重型机械学院,获双学士学位,主要研究方向为大功率随动控制系统设计工作.
更新日期/Last Update: 2009-05-05