A Feed‐Forward Wavelet Neural Network Adaptive Observer‐Based Fault Detection Technique for Spacecraft Attitude Control Systems. Issue 1 (1st January 2018)

• Record Type: Journal Article
• Authors: Xin, WEN; WANG, Jiayi; LI, Xin
• Is Part Of: Chinese journal of electronics. Volume 27:Issue 1(2018)
• Page Start: 102
• Page End: 108
• Publication Date: 2018-01-01
• Subjects: Single hidden layer feed‐forward wavelet neural network -- Fault detection -- Nonlinear system -- Adaptive observer.; adaptive control -- attitude control -- backpropagation -- control system synthesis -- fault tolerant control -- feedforward neural nets -- Lyapunov methods -- neurocontrollers -- nonlinear control systems -- space vehicles; feedforward wavelet neural network -- adaptive observer‐based fault detection technique -- spacecraft attitude control systems -- nonlinear systems -- adaptive observer design -- network convergence -- network weights -- Lyapunov function -- modified backpropagation algorithm -- stability; Electronics -- Periodicals; Electronics -- China -- Periodicals; Electronics; China; Periodicals; 621.38105
• DOI: 10.1049/cje.2017.11.010
• Languages: English
• ISSNs: 1022-4653

Abstract

Abstract : This paper presents a novel neural network‐based fault detection technique applicable to a class of nonlinear systems. The adaptive observer was designed for fault detection based on a single hidden layer feed‐forward wavelet neural network. In order to guarantee network convergence, the network weights are updated according to a modified back‐propagation algorithm, and the Lyapunov function is introduced to ensure stability. The proposed fault detection scheme was tested on the actuators of a typical spacecraft attitude control system, and the results demonstrated the effectiveness and feasibility of the proposed observer in detecting nonlinear system failure.