Longlong Liu
Least square algorithm based on bias compensated principle for parameter estimation of canonical state space model
Liu, Longlong; Long, Zhen; Azar, Ahmad Taher; Zhu, Quanmin; Ibraheem, Ibraheem Kasim; Humaidi, Amjad J
Authors
Zhen Long
Ahmad Taher Azar
Quan Zhu Quan.Zhu@uwe.ac.uk
Professor in Control Systems
Ibraheem Kasim Ibraheem
Amjad J Humaidi
Abstract
Due to the existence of system noise and unknown state variables, it is difficult to realize unbiased estimation with minimum variance for the parameter estimation of canonical state space model. This paper presents a new least squares estimator based on bias compensation principle to solve this problem, transforms canonical state space into the form suitable for the least square algorithm, introduces an augmented parameter vector and an auxiliary variable, derives parameter estimation formula based on noise compensation, realizes the unbiased estimation, and gives the specific algorithm. A simulation example is provided to verify the effectiveness of the estimator.
Citation
Liu, L., Long, Z., Azar, A. T., Zhu, Q., Ibraheem, I. K., & Humaidi, A. J. (2022). Least square algorithm based on bias compensated principle for parameter estimation of canonical state space model. Measurement and Control, 55(5-6), https://doi.org/10.1177/00202940211064179
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 25, 2021 |
Online Publication Date | Jun 1, 2022 |
Publication Date | Jun 1, 2022 |
Deposit Date | Jun 27, 2022 |
Publicly Available Date | Jun 27, 2022 |
Journal | Measurement and Control (United Kingdom) |
Print ISSN | 0020-2940 |
Electronic ISSN | 2051-8730 |
Publisher | SAGE Publications (UK and US) |
Peer Reviewed | Peer Reviewed |
Volume | 55 |
Issue | 5-6 |
DOI | https://doi.org/10.1177/00202940211064179 |
Keywords | Applied Mathematics, Control and Optimization, Instrumentation |
Public URL | https://uwe-repository.worktribe.com/output/9645625 |
Publisher URL | https://journals.sagepub.com/home/mac |
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Least square algorithm based on bias compensated principle for parameter estimation of canonical state space model
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Copyright Statement
Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License
(https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without
further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-
us/nam/open-access-at-sage).
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