Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (13): 242-244.DOI: 10.3778/j.issn.1002-8331.2010.13.072

• 工程与应用 • Previous Articles     Next Articles

Tuning PID parameters based on chaotic immune genetic algorithms

WANG Xian-fang1,2,DU Zhi-yong3,PAN Feng1   

  1. 1.School of Communication and Control Engineering,Jiangnan University,Wuxi,Jiangsu 214122,Chin a
    2.Department of Information Engineering,Henan Institute of Science and Technology,Xinxiang,Henan 453003,China
    3.Henan Mechanical and Electrical Engineering College,Xinxiang,Henan 453002,China
  • Received:2008-11-03 Revised:2009-02-16 Online:2010-05-01 Published:2010-05-01
  • Contact: WANG Xian-fang

基于混沌免疫遗传算法整定PID参数

王鲜芳1,2,杜志勇3,潘 丰1   

  1. 1.江南大学 通信与控制工程学院 自动化研究所,江苏 无锡 214122
    2.河南科技学院 信息工程系,河南 新乡453003
    3.河南机电高等专科学校,河南 新乡453002
  • 通讯作者: 王鲜芳

Abstract: According to the shortcoming of slow speed of PID parameters by using the traditional immune genetic algorithm,an intelligent PID parameters tuning method is designed through using the ideas of chaotic proliferation and the isolation niche technology,combining the characteristics of immune genetic algorithm.This method can be more effective in regional and local convergence and can jump out at a faster speed to the global optimum value of convergence,thereby better to deal with the problem that a genetic algorithm is usually encountered in the“premature” through using the sensitivity,randomness,periodicity and regularity of the proliferation of chaos to the initial value;and it not only makes the evolution of sub-population relate closely to the evolution of the entire-population,but also keeps the independence of its own evolution by adopting Niche separation technology,which is conducive to maintain the diversity of individual stocks.Adopting this method to optimize the PID parameters,the result shows that the algorithm can remarkably improve the convergence performance and search efficiency of the immune genetic algorithm.

Key words: PID control, chaotic, immune genetic algorithm, parameter optimization

摘要: 针对传统免疫遗传算法PID参数整定速度慢的缺点,通过引入了混沌增殖思想和隔离小生境技术,结合免疫遗传算法的特点,设计了一种智能的PID参数整定方法。该方法利用混沌增殖对初值的敏感性以及随机性、遍历性、规律性,使免疫遗传算法能够更加有效地跳出局部收敛区域而以更快的速度向全局最优值收敛,进而较好地处理了通常遗传算法中遇到的“早熟”问题。通过隔离小生境技术的引入使得子种群的进化不仅同整个种群的进化密切相关,还有自身进化的独立性,这有利于种群个体多样性的保持。通过实际PID参数整定的例子,结果表明该算法能明显改善免疫遗传算法的收敛性能,搜索效率也得到了显著提高。

关键词: PID控制, 混沌, 免疫遗传算法, 参数优化

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