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Unbiased Parameter Estimation via DREM with Annihilators

2024/03/17 by Anton Glushchenko, Glushchenko, Anton, Konstantin Lastochkin +1
Engineering · Physics and Astronomy · #FOS: Electrical engineering #Model Reduction and Neural Networks #Non-Destructive Testing Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2403.11076

openalex publication_date 2024/03/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In adaptive control theory, the dynamic regressor extension and mixing (DREM) procedure has become widespread as it allows one to describe major of adaptive control problems in unified terms of the parameter estimation problem of a regression equation with a scalar regressor. However, when the system/parameterization is affected by perturbations, the estimation laws, which are designed on the basis of such equation, asymptotically provides only biased estimates. In this paper, based on the bias-eliminated least-squares (BELS) approach, a modification of DREM procedure is proposed to annihilate perturbations asymptotically and, consequently, asymptotically obtain unbiased estimates. The theoretical results are supported with mathematical modelling and can be used to design adaptive observers and control systems.

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