Exact Asymptotic Estimation of Unknown Parameters of Perturbed LRE with Application to State Observation

2023/10/21 by Anton Glushchenko, Glushchenko, Anton, Konstantin Lastochkin +1
Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #FOS: Mathematics #Fault Detection and Control Systems #Statistics Theory (math.ST) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2310.14073

openalex publication_date 2023/10/21 · openalex created_date 2023/10/25 · openalex updated_date 2026/07/28

Abstract

Most identification laws of unknown parameters of linear regression equations (LRE) ensure only boundedness of a parametric error in the presence of additive perturbations, which is almost always unacceptable for practical scenarios. In this paper, a new identification law is proposed to overcome this drawback and guarantee asymptotic convergence of the unknown parameters estimation error to zero in case the mentioned additive perturbation meets special averaging conditions. Such law is successfully applied to state reconstruction problem. Theoretical results are illustrated by numerical simulations.

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