Fuzzy Adaptive Observer-Based Fault and Disturbance Reconstructions for T-S Fuzzy Systems
Yunfei Mu, Huaguang Zhang, He Ren, Yuliang Cai
Abstract
This brief focuses on the observer-based state, fault and disturbance reconstructions for Takagi-Sugeno (T-S) fuzzy-approximation-based nonlinear dynamics subject to an enlarged class of disturbances and abrupt actuator fault. By developing a brand-new fuzzy adaptive observer (FAO), unknown system state, fault and disturbance can be reconstructed simultaneously, where some classic assumptions imposed on the disturbance such as the first-order derivative being equal to zero or generation from an exogenous system are removed successfully in our work. Significantly, to reduce the conservatism, the stability criterion of error dynamic is inferred in terms of using fuzzy Lyapunov functions, and expressed in a linear matrix inequality (LMI) framework. At last, simulation study on a real plant is provided to illustrate the practicability of the given procedure.