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State estimation for a locally unobservable parameter-varying system: one gradient-based and one switched solutions

Stanislav Aranovskiy 1 Denis Efimov 2 Dmitry Sokolov 3 Jian Wang 4 Igor Ryadchikov 5 Alexey Bobtsov 6
2 VALSE - Finite-time control and estimation for distributed systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
3 ALICE - Geometry and Lighting
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
Abstract : This work is motivated by a case study of a mechanical system where a sensor bias yields loose of observability for certain values of time-varying parameters. Two solutions are proposed: a nonlinear gradient-based observer that requires the persistency of excitation of the system trajectories and a switched observer that imposes an average dwell-time requirement. For both observers, asymptotic convergence of the estimates is proven. The theoretical results are supported by illustrative numerical simulations.
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https://hal.inria.fr/hal-02634576
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Submitted on : Wednesday, May 27, 2020 - 3:45:19 PM
Last modification on : Thursday, June 11, 2020 - 4:19:48 AM

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Stanislav Aranovskiy, Denis Efimov, Dmitry Sokolov, Jian Wang, Igor Ryadchikov, et al.. State estimation for a locally unobservable parameter-varying system: one gradient-based and one switched solutions. IFAC 2020 - 21rst IFAC World Congress, Jul 2020, Berlin, Germany. ⟨hal-02634576⟩

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