文献类型：会议论文

英文题名：Variable structure control based on the fuzzy neural networks

作者：Xiao, Huimin[1];Su, Chunyi[2];Xie, Wenfang[2]

第一作者：肖会敏

通讯作者：Xiao, HM[1]

机构：[1]Henan Univ Finance & Econ, Dept Comp Sci, Zhengzhou 450002, Peoples R China;[2]Concordia Univ, Dept Mech & Ind Engn, Montreal, PQ H3G 1M8, Canada

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]corresponding author), Henan Univ Finance & Econ, Dept Comp Sci, Zhengzhou 450002, Peoples R China.|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

会议论文集：Annual Meeting of the North-American-Fuzzy-Information-Processing-Society

会议日期：JUN 03-06, 2006

会议地点：Montreal, CANADA

语种：英文

外文关键词：Controllers - Fuzzy inference - Fuzzy logic - Learning algorithms - Lyapunov functions - Sliding mode control - System stability - Variable structure control

摘要：In this paper, the fuzzy neural network is applied in the sliding mode control. The fuzzy neural network is of the fuzzy logic reasoning ability and the neural network learning ability. The physics meaning of the fuzzy neural network is clear and intelligible. According to the Sugeno reasoning method and the connecting thought, the fuzzy neural network is designed. For the sliding mode control characteristic, the construction of whole control system is designed by means of combining the fuzzy neural network applied in control and the fuzzy neural network applied in identification. The learning algorithm for neural network is also given. The chattering is efficaciously eliminated, because the control signal may be smoothed by the fuzzy neural network sliding mode controller. And its robustness is stronger than that of the common sliding mode variable structure controller. At the same time, the bounded of system uncertainty and disturbance needn't to be known in designing of the fuzzy neural network sliding mode controller. The stability of system is investigated by constructing Lyapunov function. Theorem of system global stability is summarized.