Observer Design Based on Self-Recurrent Consequent-Part Fuzzy Wavelet Neural Network  

作　　者：Xin Wen Xin Li 

机构地区：[1]Department of Aeronautics and Astronautics, Shenyang Aerospace University, Shenyang 110136, China [2]School Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

出　　处：《Tsinghua Science and Technology》2016年第5期544-551,共8页清华大学学报（自然科学版（英文版）

摘　　要：In this paper, we propose and construct an observer design based on a Self-Recurrent Consequent-Part Fuzzy Wavelet Neural Network（SRCPFWNN） for a class of nonlinear system. We use a Self-Recurrent Wavelet Neural Network（SRWNN） to construct a self-recurrent consequent part for each rule of the Takagi-Sugeno-Kang（TSK） model in the SRCPFWNN and analyze the structure of the fuzzy wavelet neural network model. Based on the Direct Adaptive Control Theory（DACT） and a back propagation-based learning algorithm, all parameters of the consequent parts are updated online in the SRCPFWNN. On this basis, we propose a design method using an adaptive state observer based on an SRCPFWNN for nonlinear systems. Using the Lyapunov function, we then prove the stability of this observer design method. Our simulation results confirm that the observer can accurately and quickly estimate the state values of the system.In this paper, we propose and construct an observer design based on a Self-Recurrent Consequent-Part Fuzzy Wavelet Neural Network（SRCPFWNN） for a class of nonlinear system. We use a Self-Recurrent Wavelet Neural Network（SRWNN） to construct a self-recurrent consequent part for each rule of the Takagi-Sugeno-Kang（TSK） model in the SRCPFWNN and analyze the structure of the fuzzy wavelet neural network model. Based on the Direct Adaptive Control Theory（DACT） and a back propagation-based learning algorithm, all parameters of the consequent parts are updated online in the SRCPFWNN. On this basis, we propose a design method using an adaptive state observer based on an SRCPFWNN for nonlinear systems. Using the Lyapunov function, we then prove the stability of this observer design method. Our simulation results confirm that the observer can accurately and quickly estimate the state values of the system.

关 键 词：Takagi-Sugeno-Kang （TSK） fuzzy model activation functions state observer nonlinear systems simulation 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TP183[自动化与计算机技术—控制科学与工程]