基于混沌遗传算法的PID参数优化  

Optimization Control of PID Based on Chaos Genetic Algorithm

作　　者：伍铁斌[1] 成运[1] 周桃云[1] 岳舟[1] 

机构地区：[1]湖南人文科技学院通信与控制工程系,湖南娄底417600

出　　处：《计算机仿真》2009年第5期202-204,226,共4页Computer Simulation

基　　金：湖南省重点学科建设项目资助;湖南省自然科学基金项目资助(07JJ6116)

摘　　要：随着计算机技术的飞跃发展和人工智能技术渗透到自动控制领域,各种先进PID控制器参数整定方法层出不穷,给PID控制器参数整定的研究带来了无限活力和契机;然而很多先进的PID参数整定方法并没有像预期的那样产生完美的控制效果。将遗传算法和混沌优化方法智能集成,利用混沌序列的"遍历性、随机性、规律性"的特点生成初始种群,在遗传操作中加入混沌细搜索,大大提高了局部搜索能力,能有效防止遗传算法陷入局部最优和发生早熟现象,仿真表明,混沌遗传算法优化结果相当理想,效果令人满意,优于常规的遗传算法。With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameter tuning methods of PID controller are emerging endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfectly as expected. The paper integrates GA with chaos optimization, using the chaos serial＇ s property of ＂ergodicity, randomicity, regularity＂ to generate original population. Adding chaotic fine search to genetic operaton to greatly improve the local search ability, which avoids local optimization and premature convergence. The results of the simulation demonstrate that the chaos genetic algorithm has ideal and satisfied optimization result and is much better than the common Genetic Algorithm.

关 键 词：混沌遗传算法 遗传算法 比例积分微分 控制 

分 类 号：TP273.1[自动化与计算机技术—检测技术与自动化装置]