模糊神经控制器在复杂系统中的应用研究  

The application of self-adaptive fuzzy neural controller in complicated system

作　　者：王建辉[1] 王艳秋[2] 

机构地区：[1]沈阳大学信息工程学院 [2]辽宁工学院

出　　处：《沈阳大学学报》2004年第2期6-10,共5页

基　　金：国家自然科学基金资助项目(60274024)

摘　　要：首先提出一种适用于复杂系统的自适应模糊控制器.针对该控制器在应用于复杂系统时,模糊规则过多及建立规则的时间随规则数增加而以指数规律增长的问题,提出了另一种适用于复杂系统的自适应模糊神经控制器.该控制器采用“全逼近”的控制策略,依据李亚普诺夫方法给出了模糊神经自适应输出反馈控制律及参数自适应律.仿真研究证明了复杂系统的稳定性以及跟踪误差的收敛性.Proposes a self-adaptive fuzzy controller for complicated system first. Aiming at the problems of it such as the numerous fuzzy rules and the time of founding rules increases exponentially corresponding with the increase of the number of rules, another self-adaptive fuzzy neural controller for complicated system is proposed. The method of 'full approximation' is adopted in this controller. The laws of output feedback control and parameter self-adaptive are derived by approach of Lyapunov functon. The stability of the complicated system and the convergence of the tracking errors are proved by simulation study.

关 键 词：模糊神经控制器 控制量校正 控制规则修正 稳定性 

分 类 号：O231[理学—运筹学与控制论]