%0 Journal Article
%T A New Fuzzy Identification Method for Complex Systems<br>一种新的复杂系统模糊辨识方法
%A Zhang Ping''an
%A Li Renhou
%A <br>张平安
%A 李人厚
%J 自动化学报
%D 1997
%I 
%X In this paper ,a new fuzzy model is presented to overcome the difficulty of using the first order Takagi Sugeno model to identify complex systems. The structure of the new model is based on the first order Takagi Sugeno model, but a nonlinear mapping is added to. In order to realize the model, a fuzzy neural network(FNN) with Kalman filter algorithm is then implemented. Simulation results show that this method is very efficient and practical.
%K Fuzzy identificatioin
%K fuzzy neural network
%K system identification<br>模糊辨识
%K 神经元网络
%K 系统辨识
%K 复杂系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=5425746684C580472E244989544BA320&yid=5370399DC954B911&vid=EA389574707BDED3&iid=B31275AF3241DB2D&sid=92DE343A8428AA81&eid=08F83145FA367D52&journal_id=0254-4156&journal_name=自动化学报&referenced_num=5&reference_num=2