%0 Journal Article
%T ROBUST ADAPTIVE TRACKING CONTROL FOR NONLINEAR SYSTEMS BASED ON SELF-ORGANIZING FUZZY CMAC NEURAL NETWORKS<br>基于自组织模糊CMAC网络的非线性系统鲁棒自适应跟踪控制
%A WANG Yuan
%A HU Shou-Song
%A <br>王源
%A 胡寿松
%J 自动化学报
%D 2002
%I 
%X This paper presents a method of robust adaptive tracking control for nonlinear systems based on a self organizing fuzzy CMAC neural network. The on line learning while controlling neural network is used to adaptively regulate the error in the plant inversion which may be due to modeling uncertainties and disturbances in order to make the system outputs accurately track the outputs of the reference model. The updating rule of SOFCMAC weights is derived from Lyapunov stability theory. The stability of the designed system is proved. Simulation results demonstrate the effectiveness of the proposed method.
%K Dynamic inversion
%K nonlinear
%K CMAC
%K adaptive control<br>自组织模糊CMAC网络
%K 非线性系统
%K 鲁棒自适应跟踪控制
%K 动态逆
%K 自适应控制
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=A912BD5934BD48B1&yid=C3ACC247184A22C1&vid=D3E34374A0D77D7F&iid=B31275AF3241DB2D&sid=CEA1F7DC6B978724&eid=A73A882009D0AEFE&journal_id=0254-4156&journal_name=自动化学报&referenced_num=4&reference_num=5