Fuzzy extended state observer for the fault detection and identification.

This paper introduces a novel methodology to detect and identify faults for a class of autonomous nonlinear systems. In the proposed design, a fuzzy extended system observer (FESO) based on the Mandami-type fuzzy system is used to estimate the fault that is considered to be the extended system state. In this method, the Mamdani-type fuzzy system is based on a single-input single-output (SISO) where the observer error is considered as the fuzzy input variable. Additionally, the stability analysis under Lyapunov criteria verifies that the solutions of proposed FESO are ultimately bounded. Finally, simulation examples are given to corroborate the feasibility of the proposed FESO. • This paper presents a novel fuzzy extended state observer in order to solve the fault detection and identification problem. • The proposed observer is based on a single-input single-outpu Mamdani-type fuzzy inference system. • The Lyapunov study assures that the solutions of the proposed FESO are ultimately bounded. • The tuning of the fuzzy system, allows to achieve a family of fuzzy gains and improves the rate of convergence. • Numerical simulations confirm the theoretical results. [ABSTRACT FROM AUTHOR]