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

Hector Rios, Denis Efimov, Jaime A. Moreno, Wilfrid Perruquetti, Juan G. Rueda-Escobedo

Research output: Contribution to journalArticle

24 Scopus citations


© 1963-2012 IEEE. 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.
Original languageAmerican English
Pages (from-to)3671-3678
Number of pages8
JournalIEEE Transactions on Automatic Control
StatePublished - 1 Jul 2017
Externally publishedYes

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