Adaptive observer-based fault diagnosis for a class of MIMO nonlinear uncertain systems

In this paper, a high-gain nonlinear observer based fault diagnosis approach is proposed for a general class of nonlinear uncertain systems. The nonlinear system under consideration contains parameter uncertainties as well as Lipschitz-like nonlinearities and may be harmed by time-varying fault. The fault diagnosis algorithm is designed based on a new adaptive estimation method for estimation of the parameters related to faults. The main result is given in a constructive manner by developing a novel nonlinear adaptive observer, without resort to any linearization. The design of the proposed observer does not necessitate the resolution of any dynamics systems and its expression is explicitly given. Its global exponential convergence is ensured, which does not rely on solving any kind of dynamic Riccati equation. A simulation example is given to illustrate the efficiency of the proposed fault diagnosis method.