Actuator fault diagnosis for uncertain T–S fuzzy systems with local nonlinear models

Abstract

This article investigates the problem of fault diagnosis (FD) for a class of nonlinear state-feedback control systems subject to parameter uncertainties. The considered nonlinear systems are described by T–S fuzzy models with local nonlinear parts and uncertain grades of membership. First, a general actuator fault model is proposed, which considers bias faults and gain faults. Then, a switching technique is introduced to address the unknown membership functions, external disturbances, faults, and their coupling. Furthermore, an adaptive FD observer design method combined with the switching technique is proposed to estimate the occurred actuator fault. It is noted that the obtained fault errors converge exponentially to zero. Finally, a numerical example of NSV reentry dynamic model is given to confirm the effectiveness of the new results.