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Time-Varying Parameter Identification Algorithms: Finite and Fixed-Time Convergence
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.
Cited literature [24 references]
https://hal.inria.fr/hal-01470957
Contributor : Denis Efimov <>
Submitted on : Saturday, February 18, 2017 - 9:36:29 AM
Last modification on : Monday, December 14, 2020 - 5:38:23 PM
Long-term archiving on: : Friday, May 19, 2017 - 12:13:22 PM
Contributor : Denis Efimov <>
Submitted on : Saturday, February 18, 2017 - 9:36:29 AM
Last modification on : Monday, December 14, 2020 - 5:38:23 PM
Long-term archiving on: : Friday, May 19, 2017 - 12:13:22 PM
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_LTV_ParIdent_FxT_TAC_FV.pdf
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