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Bias compensation-based parameter and state estimation for a class of time-delay non-linear state-space models

Gu, Ya; Zhu, Quanmin; Nouri, Hassan

Bias compensation-based parameter and state estimation for a class of time-delay non-linear state-space models Thumbnail


Authors

Ya Gu

Quanmin Zhu

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Hassan Nouri Hassan.Nouri@uwe.ac.uk
Reader in Electrical Power and Energy



Abstract

This study presents, based on bias compensation, an integrated parameter and state estimation algorithm for a class of time-delay non-linear systems which are described by canonical observable state-space model. In technical development, the state-space system model is transformed into an input-output representation/realisation by eliminating the state variables, which is accordingly used as a feasible identification model. With such an input-output structure, directly data measurable to accommodate the estimation bias, an augmented least-squares algorithm (by adding the bias correction terms into the estimates) is proposed for estimating the parameters and states interactively. Regarding the estimator properties, the proposed algorithm is proved unbiased. The simulation results show that the proposed algorithm has good performance in estimating the parameters of state-space systems.

Citation

Gu, Y., Zhu, Q., & Nouri, H. (2020). Bias compensation-based parameter and state estimation for a class of time-delay non-linear state-space models. IET Control Theory and Applications, 14(15), 2176-2185. https://doi.org/10.1049/iet-cta.2020.0104

Journal Article Type Article
Acceptance Date Sep 9, 2020
Online Publication Date Aug 14, 2020
Publication Date Oct 15, 2020
Deposit Date Oct 18, 2020
Publicly Available Date Oct 28, 2020
Journal IET Control Theory & Applications
Print ISSN 1751-8644
Electronic ISSN 1751-8652
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 14
Issue 15
Pages 2176-2185
DOI https://doi.org/10.1049/iet-cta.2020.0104
Keywords Control and Systems Engineering; Human-Computer Interaction; Electrical and Electronic Engineering; Control and Optimization; Computer Science Applications
Public URL https://uwe-repository.worktribe.com/output/6742767

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