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Article Dans Une Revue Journal of Physics: Conference Series Année : 2017

Robust unknown input observer design for state estimation and fault detection using linear parameter varying model

Résumé

This paper proposes a robust unknown input observer for state estimation and fault detection using linear parameter varying model. Since the disturbance and actuator fault is mixed together in the physical system, it is difficult to isolate the fault from the disturbance. Using the state transforation, the estimation of the original state becomes to associate with the transform state. By solving the linear matrix inequalities (LMIs) and linear matrix equalities (LMEs), the parameters of the UIO can be obtained. The convergence of the UIO is also analysed by the Layapunov theory. Finally, a wind turbine system with disturbance and actuator fault is tested for the proposed method. From the simulations, it demonstrates the effectiveness and performances of the proposed method.

Dates et versions

hal-01688792 , version 1 (19-01-2018)

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Citer

S.Z. Li, Haoping Wang, A. Aitouche, Y. Tian, N. Christov. Robust unknown input observer design for state estimation and fault detection using linear parameter varying model. Journal of Physics: Conference Series, 2017, 13th European Workshop on Advanced Control and Diagnosis (ACD) Nov 2016 Lille, 783, pp.012001-1-9. ⟨10.1088/1742-6596/783/1/012001⟩. ⟨hal-01688792⟩
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