Time-Varying Parameter Identification Algorithms: Finite and Fixed-Time Convergence

H Ríos 1 Denis Efimov 2 Jaime Moreno 3 Wilfrid Perruquetti 2, 4 J Rueda-Escobedo 3
1 University of California [Santa Barbara]
2 NON-A - Non-Asymptotic estimation for online systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
3 UNAM - Universidad Nacional Autónoma de México
4 Ecole Centrale de Lille
Abstract : In this paper the problem of time-varying parameter identification is studied. To this aim, two identification algorithms are developed in order to identify time-varying parameters in a finite-time or prescribed time (fixed-time). The convergence proofs are based on a notion of finite-time stability over finite intervals of time, i.e. Short-finite-time stability; homogeneity for time-varying systems; and Lyapunov-based approach. The results are obtained under injectivity of the regressor term, which is related to the classical identifiability condition. The case of bounded disturbances (noise of measurements) is analyzed for both algorithms. Simulation results illustrate the feasibility of the proposed algorithms.
Keywords : Finite/Fixed-time Time-varying systems Parameter identification
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Article dans une revue
IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2018
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H Ríos, Denis Efimov, Jaime Moreno, Wilfrid Perruquetti, J Rueda-Escobedo. Time-Varying Parameter Identification Algorithms: Finite and Fixed-Time Convergence. IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2018. 〈hal-01470957〉

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