Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises
By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output-error-like syst...
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| Published in: | IET signal processing Vol. 14; no. 7; pp. 455 - 466 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
The Institution of Engineering and Technology
01.09.2020
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| Subjects: | |
| ISSN: | 1751-9675, 1751-9683, 1751-9683 |
| Online Access: | Get full text |
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| Abstract | By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output-error-like system with autoregressive moving average noise from input–output data. The key is to divide the identification model into several submodels based on the hierarchical identification principle and to establish the parameter estimation algorithm by using the coupled relationship between these submodels. The simulation test results indicate that the proposed algorithms are effective. |
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| AbstractList | By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output‐error‐like system with autoregressive moving average noise from input–output data. The key is to divide the identification model into several submodels based on the hierarchical identification principle and to establish the parameter estimation algorithm by using the coupled relationship between these submodels. The simulation test results indicate that the proposed algorithms are effective. |
| Author | Pan, Jian Zhang, Xiao Chang, Yufang Sheng, Jie Liu, Qinyao Ding, Feng Ma, Hao |
| Author_xml | – sequence: 1 givenname: Jian orcidid: 0000-0002-5545-7433 surname: Pan fullname: Pan, Jian organization: 1Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, People's Republic of China – sequence: 2 givenname: Hao orcidid: 0000-0001-9212-3363 surname: Ma fullname: Ma, Hao organization: 1Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, People's Republic of China – sequence: 3 givenname: Xiao surname: Zhang fullname: Zhang, Xiao organization: 2School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, People's Republic of China – sequence: 4 givenname: Qinyao surname: Liu fullname: Liu, Qinyao organization: 2School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, People's Republic of China – sequence: 5 givenname: Feng orcidid: 0000-0002-2721-2025 surname: Ding fullname: Ding, Feng email: fding@jiangnan.edu.cn organization: 2School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, People's Republic of China – sequence: 6 givenname: Yufang surname: Chang fullname: Chang, Yufang organization: 1Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, People's Republic of China – sequence: 7 givenname: Jie surname: Sheng fullname: Sheng, Jie organization: 3School of Engineering and Technology, University of Washington, Tacoma, Washington 98402, USA |
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| Keywords | least squares approximations coupled relationship coupling identification concept autoregressive moving average processes coloured noises stochastic gradient algorithm parameter estimation algorithm projection algorithm input–output data identification autoregressive moving average noise multivariable control systems gradient search identification model hierarchical identification principle parameter estimation multivariable output-error-like system stochastic processes gradient methods recursive coupled projection algorithms state-space methods |
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| SubjectTerms | autoregressive moving average noise autoregressive moving average processes coloured noises coupled relationship coupling identification concept gradient methods gradient search hierarchical identification principle identification identification model input–output data least squares approximations multivariable control systems multivariable output‐error‐like system parameter estimation parameter estimation algorithm projection algorithm recursive coupled projection algorithms Research Article state‐space methods stochastic gradient algorithm stochastic processes |
| Title | Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises |
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