A NEW APPROACH OF FAULT DETECTION BASED ON WAVEARX NEURAL NETWORK OBSERVER

A novel approach based on WaveARX neural network observer is proposed far the fault detect of a class of nonlinear systems which consist of known linear part and unknown nonlinear part. A linear observer is first designed, then a nonlinear compensation term in the nonlinear observer is estimated by using a deconvolution method. The WaveARX network is used to model the obtained compensation term. At last, the residual fur fault detection is generated based on the analysis of the upper bound approximate error. Simulation results have shown the feasibility and effectiveness of the method.