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Robust adaptive stabilization by delay under state parametric uncertainty and measurement bias

Jian Wang 1 Stanislav Aranovskiy 2, 3 Emilia Fridman 4 Dmitry Sokolov 5 Denis Efimov 6 Alexey Bobtsov 7
5 Pixel
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
6 VALSE - Finite-time control and estimation for distributed systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : An output robust adaptive control is designed for a class of Lipschitz nonlinear systems under assumption that the measurements are available with a constant bias and the state equations linearly parameterized by unknown parameters and external disturbances. A dynamic state reconstruction (synthesis of an observer) is avoided by using delayed values of the output in the feedback and adaptation laws. The analysis of robust stability for the resulted time-delay system is performed by using the Lyapunov-Krasovskii approach. The control and adaptation gains can be selected as a solution of the proposed linear matrix inequalities. This research is motivated by a nonlinear pendulum control problem, and the efficacy of the developed control is demonstrated on this application through experiments.
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https://hal.inria.fr/hal-03059893
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Submitted on : Sunday, December 13, 2020 - 1:28:55 PM
Last modification on : Saturday, January 16, 2021 - 3:29:07 AM

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Jian Wang, Stanislav Aranovskiy, Emilia Fridman, Dmitry Sokolov, Denis Efimov, et al.. Robust adaptive stabilization by delay under state parametric uncertainty and measurement bias. IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TAC.2020.3045125⟩. ⟨hal-03059893⟩

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