Skip to Main content Skip to Navigation
Journal articles

Accelerated convergence with improved robustness for discrete-time parameter estimation

Abstract : The dynamic regressor extension and mixing (DREM) method provides a fixedtime converging parameter estimator for persistently excited regressor under bounded measurement noises. This note aims to develop this approach for cases with weaker excitation and regressor constraints. Several nonlinear estimation schemes with fixed-time convergence rates and improved measurement noise robustness properties are proposed here.
Complete list of metadata

https://hal-centralesupelec.archives-ouvertes.fr/hal-03760746
Contributor : Stanislav Aranovskiy Connect in order to contact the contributor
Submitted on : Thursday, August 25, 2022 - 4:57:35 PM
Last modification on : Sunday, August 28, 2022 - 3:46:18 AM

File

Accelerated_convergence_SCL_R0...
Files produced by the author(s)

Identifiers

Citation

Stanislav Aranovskiy, Rosane Ushirobira, Denis Efimov, Jian Wang. Accelerated convergence with improved robustness for discrete-time parameter estimation. Systems and Control Letters, Elsevier, 2022, 55 (12), pp.324-329. ⟨10.1016/j.sysconle.2022.105344⟩. ⟨hal-03760746⟩

Share

Metrics

Record views

70

Files downloads

5