Robust Fault Detection and Estimation for Descriptor Systems Based on Multi-Models Concept

Abstract : This paper addresses the robust fault detection and estimation problem of nonlinear descriptor system with unknown inputs observers. The considered nonlinear descriptor system is transformed into an equivalent multi-models form by using the Takagi-Sugeno (T-S) approach. Two cases are considered: the first one deals with the multi-models based on measurable decision variables and the second one assumes that these decision variables are unmeasurable. Then, a residual generator based on an unknown observer is designed for both fault detection and estimation. Stability analysis and gain matrices determination are performed by resolving a set of Linear Matrices Inequalities (LMIs) for both cases. The performances of the proposed fault detection and estimation method is successfully applied to an electrical circuit.
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International Journal of Control, Automation and Systems, Springer, 2012, 10 (6), pp.1260-1266. 〈10.1007/s12555-012-0622-z〉
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Habib Hamdi, Mickael Rodrigues, Chokri Mechmeche, Naceur Benhadj Braiek. Robust Fault Detection and Estimation for Descriptor Systems Based on Multi-Models Concept. International Journal of Control, Automation and Systems, Springer, 2012, 10 (6), pp.1260-1266. 〈10.1007/s12555-012-0622-z〉. 〈hal-00752421〉

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