%0 Journal Article
%T Fault Estimation and Accommodation for a Class of Nonlinear System Based on Neural Network Observer
%A Wang Ruonan
%A Jiang Bin
%A Liu Jianwei
%J 南京理工大学学报
%D 2018
%R 10.16356/j.1005-1120.2018.02.318
%X The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied using adaptive observer and neural network techniques. A robust adaptive learning algorithm based on switching βs-modification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults. Then a fault tolerant controller is designed to restore system performance. Dynamic error convergence and system stability can be guaranteed by Lyapunov stability theory. Finally, simulation results of quadrotor helicopter attitude systems are presented to illustrate the efficiency of the proposed techniques.
%K actuator fault
%K component fault
%K neural network
%K adaptive observer
%K fault tolerant controller
%U http://tnuaa.nuaa.edu.cn/ch/reader/view_abstract.aspx?file_no=20180212&flag=1