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Article Dans Une Revue Journal of The Franklin Institute Année : 2020

Optimal Reset Unknown Input Observer Design for Fault and State Estimation in a Class of Nonlinear Uncertain Systems

Résumé

This paper proposes a novel kind of Unknown Input Observer (UIO) called Reset Unknown Input Observer (R-UIO) for state and fault estimation of a class of nonlinear uncertain systems using linear matrix inequality (LMI) techniques. In the devised R-UIO, the states of the observer are reset to the after-reset value based on an optimal H ∞ reset law in order to decrease the L 2 norm and settling time of estimation error. It is shown that the utilization of such an observer can significantly improve the transient response of the observer. Moreover, the devised approach can be applied to both SISO and MIMO systems. Furthermore, the robust stability analysis of the devised R-UIO is addressed. Finally, the capabilities of the proposed method are demonstrated by applying it to a Continuous Stirred-Tank Reactor (CSTR) as a practical model.
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Dates et versions

hal-03014495 , version 1 (19-11-2020)

Identifiants

Citer

Iman Hosseini, Mirko Fiacchini, Paknoush Karimaghaee, Alireza Khayatian. Optimal Reset Unknown Input Observer Design for Fault and State Estimation in a Class of Nonlinear Uncertain Systems. Journal of The Franklin Institute, 2020, 357 (5), pp.2978-2996. ⟨10.1016/j.jfranklin.2019.12.008⟩. ⟨hal-03014495⟩
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