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 journalArticlepeer-review

80 Scopus citations


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 languageEnglish
Article number7862827
Pages (from-to)3671-3678
Number of pages8
JournalIEEE Transactions on Automatic Control
Issue number7
StatePublished - Jul 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 1963-2012 IEEE.


  • Finite/Fixed-time (FT/FxT)
  • parameter identification
  • time-varying systems


Dive into the research topics of 'Time-Varying Parameter Identification Algorithms: Finite and Fixed-Time Convergence'. Together they form a unique fingerprint.

Cite this