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Communication Dans Un Congrès Année : 2022

Robust Observer synthesis for Bilinear Parameter Varying system

Résumé

In the present paper, sufficient conditions for the synthesis of robust Unknown Input Observers (UIOs) are proposed for a class of nonlinear systems, both in continuous and discrete time. The considered class is general enough to contain bilinear systems as well as Linear Parameter-Varying (LPV) systems with no parameter variation on the output matrix. The proposed conditions are numerically tractable, and are expressed in terms of Linear Matrix Inequalities (LMIs) or Linear Matrix Equalities (LMEs). Furthermore, the gain synthesis problem is shown to be formulated as a convex optimisation one, directly enabling the minimization of the influence of noisy measurements and model uncertainty. Simulations on energy systems are provided to illustrate the proposed methodologies.
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Dates et versions

hal-03794045 , version 1 (03-10-2022)

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Lucien Etienne, Kokou Anani Agbessi Langueh, Hassan Karkaba, Alessio Iovine. Robust Observer synthesis for Bilinear Parameter Varying system. 61st IEEE Conference on Decision and Control (CDC 2022), Dec 2022, Cancun, Mexico. ⟨10.1109/cdc51059.2022.9992459⟩. ⟨hal-03794045⟩
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