Robust fault detection for Takagi-Sugeno discrete models: Application for a three-tank system

this paper, we present a fuzzy observer based on Takagi- Sugeno (TS) models, to estimate simultaneously the system state and the sensors faults of discrete time nonlinear systems. The method uses the technique of descriptor systems, by considering the sensor faults as auxiliary states variables. More precisely, This paper addresses the problem of index fault detection observer to ensure the sensitivity against the faults. The proposed method is based on the use of the Lyapunov theory to ensure the stability of the system. Necessary and sufficient conditions are obtained in terms of Linear Matrix Inequalities (LMIs), in order to determine the observer gains. An application of the fault estimation method on an hydraulic process with three tanks, using TS models is realized. Simulation and experimental results show the effectiveness of the proposed method.

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