Skip to main content

Research Repository

Advanced Search

Second-order optimization methods for time-delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods

Chen, Jing; Pu, Yan; Guo, Liuxiao; Cao, Junfeng; Zhu, Quanmin

Second-order optimization methods for time-delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods Thumbnail


Authors

Jing Chen

Yan Pu

Liuxiao Guo

Junfeng Cao

Profile image of Quan Zhu

Quan Zhu Quan.Zhu@uwe.ac.uk
Professor in Control Systems



Abstract

This article proposes several second-order optimization methods for time-delay ARX model. Since the time-delay in the information vector makes the traditional identification algorithms be inefficient, a redundant rule based method is utilized to transformed the model into a redundant model. Then, the nature gradient descent (NGD) algorithm is developed for such a model. To reduce the computational efforts of the NGD algorithm and to adaptively update each element in the parameter vector, two modified NGD algorithms are also presented. The simulation examples verify the effectiveness of the proposed algorithms.

Journal Article Type Article
Acceptance Date Oct 8, 2022
Online Publication Date Oct 25, 2022
Publication Date Jan 1, 2023
Deposit Date Nov 8, 2022
Publicly Available Date Oct 26, 2023
Journal International Journal of Adaptive Control and Signal Processing
Print ISSN 0890-6327
Electronic ISSN 1099-1115
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 37
Issue 1
Pages 211-223
DOI https://doi.org/10.1002/acs.3519
Keywords Electrical and Electronic Engineering, Signal Processing, Control and Systems Engineering, ARX model, Time-delay, Nature gradient descent, Adaptive gradient descent, Momentum based method, Convergence rate
Public URL https://uwe-repository.worktribe.com/output/10121748
Publisher URL https://onlinelibrary.wiley.com/doi/10.1002/acs.3519

Files

Second‐order optimization methods for time‐delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods (274 Kb)
PDF

Licence
http://www.rioxx.net/licenses/all-rights-reserved

Publisher Licence URL
http://www.rioxx.net/licenses/all-rights-reserved

Copyright Statement
This is the peer reviewed version of the following article: Chen, J., Pu, Y., Guo, L., Cao, J., & Zhu, Q. (2023). Second-order optimization methods for time-delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods. International Journal of Adaptive Control and Signal Processing, 37(1), 211-223'.

DOI: https://doi.org/10.1002/acs.3519

It has been published in final form at: https://onlinelibrary.wiley.com/doi/10.1002/acs.3519

This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.






You might also like



Downloadable Citations