%0 Journal Article
%T Self-learning controller using support vector machines and fuzzy inference system<br>支持向量机-模糊推理自学习控制器设计
%A YUAN Xiao-fang
%A WANG Yao-nan
%A SUN Wei
%A <br>袁小芳
%A 王耀南
%A 孙炜
%J 控制理论与应用
%D 2006
%I 
%X As conventional fuzzy inference system (FIS) was derived from expert experience,it has poor ability in self-learning or adaptation.The self-learning capability of fuzzy inference system was realized in this paper using support vector machines(SVM),and a self-learning controller based on support vector machines-fuzzy inference system(SVM-FIS) was proposed.Both the structure and learning algorithms of the proposed self-learning controller were analyzed.Two learning algorithms of Multi-scaled Davidon-Fletcher-Powell(MDFP) method and chaotic optimization were compared.Simulation results for a nonlinear system demonstrate that the proposed self-learning controller has better control performance over fuzzy logic controller.
%K fuzzy logic
%K fuzzy inference system
%K support vector machines(SVM)
%K self-learning<br>模糊逻辑
%K 模糊推理系统
%K 支持向量机
%K 自学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=9D380AD962A0B13E&yid=37904DC365DD7266&vid=EA389574707BDED3&iid=CA4FD0336C81A37A&sid=CA4FD0336C81A37A&eid=B31275AF3241DB2D&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=5&reference_num=7