Nonlinear System Fault Diagnosis And Reconstruction Based On Sliding Mode Observers

This thesis mainly studies nonlinear system fault diagnosis and reconstruction based on sliding mode observers.Firstly, the development and current situation of fault diagnosis and reconstruction are surveyed. At the same time, the model which is studied in this paper and the design methods of sliding mode observers are introduced.Secondly, the design problem of robust sliding mode observer for a class of nonlinear uncertain systems is described. A new nonlinear robust sliding mode observer design method combined the Thau observer with Walcott-Zak observer is proposed. It is proved by Lyapunov theory that the observation error is uniformly ultimately bounded with respect to a set. Finally, the designed method is improved to multi fault detection and the simulation results demonstrate the effectiveness of the method.Thirdly, the problem of fault reconstruction for a class of uncertain nonlinear systems is studied. An adaptive fuzzy sliding mode observer is designed for fault reconstruction of a class of uncertain nonlinear systems. The simulation results demonstrate the effectiveness of the method.Finally, fault reconstruction for a class of nonlinear systems based on extended sliding mode observer is studied. Compared with traditional fault reconstruction methods, the faults and the system uncertainty are viewed as an extended system state in this method. A extended sliding mode observer is designed for the purpose of fault reconstruction based on the estimation of the extended system states. The simulation results demonstrate this method has the higher reconstruction precision than the neural-network based approach.