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

Autor:	Glushchenko, Anton, Lastochkin, Konstantin
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Systems and Control Mathematics - Statistics Theory
Druh dokumentu:	Working Paper
Popis:	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. Comment: 6 pages, 6 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2310.14073 Zobrazit plný text záznamu View this record from Arxiv