基于混沌免疫遗传算法整定PID参数  

Tuning PID parameters based on chaotic immune genetic algorithms

作　　者：王鲜芳[1,2] 杜志勇[3] 潘丰[1] 

机构地区：[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

出　　处：《计算机工程与应用》2010年第13期242-244,共3页Computer Engineering and Applications

基　　金：国家高技术研究发展计划(863)No.2006AA020301-11;河南省教育厅自然科学研究项目(No.2007510006)~~

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。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.

关 键 词：PID控制 混沌 免疫遗传算法 参数优化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]