Paper Info
Title
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.
Year
DOI
Venue
2017
10.1109/TAC.2017.2673413
IEEE Trans. Automat. Contr.
Keywords
Field
DocType
Convergence,Time-varying systems,Signal processing algorithms,Stability analysis,Noise measurement,Algorithm design and analysis,Simulation
Fixed time,Convergence (routing),Mathematical optimization,Algorithm design,Homogeneity (statistics),Noise measurement,Identifiability,Control theory,Algorithm,Mathematics,Finite time,Bounded function
Journal
Volume
Issue
ISSN
62
7
0018-9286
Citations 
PageRank 
References 
9
0.65
8
Authors
5
Name
Order
Citations
PageRank
Héctor Ríos18615.20
Denis V. Efimov269693.92
Jaime A. Moreno377170.62
Wilfrid Perruquetti4106493.15
Juan G. Rueda-Escobedo5144.96