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基于多模型粒子群优化的PID参数鲁棒整定
引用本文:郝万君,苏承慧,强文义,柴庆宣.基于多模型粒子群优化的PID参数鲁棒整定[J].信息与控制,2006,35(6):711-714.
作者姓名:郝万君  苏承慧  强文义  柴庆宣
作者单位:1. 哈尔滨工业大学航天学院,黑龙江,哈尔滨,150001;北华大学计算机科学技术学院,吉林,吉林,132021
2. 北华大学电气与信息工程学院,吉林,吉林,132021
3. 哈尔滨工业大学航天学院,黑龙江,哈尔滨,150001
摘    要:针对常规粒子群优化算法存在的鲁棒性能差的问题,提出一种基于多模型的粒子群优化方法.将其应用于对PID控制器参数的优化,有效地避免了PID控制器设计中复杂的参数调试.即使在模型失配的情况下,控制系统仍保持了良好的控制品质和鲁棒性.通过对几个典型被控对象的仿真实验,证明了所提出的优化算法的实用性、有效性和优越性.

关 键 词:PID控制  参数优化  粒子群优化  多目标  鲁棒性
文章编号:1002-0411(2006)06-0711-04
收稿时间:2006-04-21
修稿时间:2006-04-21

Robust Tuning of PID Parameters Based on Multi-model PSO
HAO Wan-jun,SU Cheng-hui,QIANG Wen-yi,CHAI Qing-xuan.Robust Tuning of PID Parameters Based on Multi-model PSO[J].Information and Control,2006,35(6):711-714.
Authors:HAO Wan-jun  SU Cheng-hui  QIANG Wen-yi  CHAI Qing-xuan
Affiliation:1. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China; 2. College of Computer Science and Technology, Beihua University, Jilin 132021, China; 3. College of Electrical and Information Engineering, Beihua University, Jilin 132021, China
Abstract:A particle swarm optimization(PSO) algorithm based on multi-model is proposed to overcome the problem of poor robustness in general PSO algorithm.The algorithm is applied to optimize the control parameters of PID and the complex adjustment of parameters in PID controller design is effectively avoided.Even in the case of model mismatch,the control system can maintain better control performance and have stronger robustness.Simulation experiments have been made on several typical controlled objects to demonstrate the practicality,effectiveness and(superiority) of the proposed optimization algorithm.
Keywords:PID control  parameter optimization  particle swarm optimization  muhiple objective  robustness
本文献已被 CNKI 维普 万方数据 等数据库收录!
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