%0 Journal Article
%T Multi-objective optimization for PID parameter based on elitist-evolution guidance
基于精英进化导向的多目标PID参数优化
%A WU Xing
%A LOU Pei-huang
%A TANG Dun-bing
%A
武星
%A 楼佩煌
%A 唐敦兵
%J 控制理论与应用
%D 2010
%I
%X For multi-objective optimization problems, a decision-maker must choose one solution from many nondominated ones in Pareto front. Decision preferences are introduced into Pareto optimization in this paper, and a multiobjective genetic algorithm based on elitist-guidance mechanism is presented. Elitists are selected from Pareto optimal solutions according to decision-making preferences. The lossless-finite-precision method and the normalized incrementdistance are proposed to keep the population diversity. The effect of decision-making preferences is spread among the entire population by using the multi-population evolution mechanism. This approach is applied successfully to PID parameter optimization of automated-guided-vehicle(AGV) servo system, which can make a fast, effective and directional search for Pareto optimal solutions according to decision-making preferences, and ensures the servo control for achieving the velocity-response performance required by path tracking.
%K PID parameter tuning
%K multi-objective optimization
%K genetic algorithm
%K elitist-guidance
%K Pareto optimal solutions
PID参数整定
%K 多目标优化
%K 遗传算法
%K 精英导向
%K Pareto最优解
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=F3CD86FBB306C31B9E3DE6CF1BEA76BA&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=9CF7A0430CBB2DFD&sid=A31F2945A5873795&eid=1C7C31A28F5ECC6F&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=10