LAUSR

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.