A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising
This paper presents a novel method to identify a class of closed-loop systems, in which both the forward channel and the feedback channel have unknown time-delays. Taking into account the time-delays, an overparameterized identification model with a sparse parameter vector is established. Based on t...
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doaj-12bf89c7b08e4cbe966f6ad322d4b0c32021-03-30T02:32:14ZengIEEEIEEE Access2169-35362020-01-018996489965410.1109/ACCESS.2020.29768629015976A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-NoisingYing Chen0https://orcid.org/0000-0002-0376-0705Yanjun Liu1https://orcid.org/0000-0002-3086-3785Jing Chen2https://orcid.org/0000-0001-5615-2255Junxia Ma3https://orcid.org/0000-0002-0151-31881Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi, China1Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi, ChinaSchool of Science, Jiangnan University, Wuxi, China1Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi, ChinaThis paper presents a novel method to identify a class of closed-loop systems, in which both the forward channel and the feedback channel have unknown time-delays. Taking into account the time-delays, an overparameterized identification model with a sparse parameter vector is established. Based on the basis pursuit de-noising criterion, the sparse parameter vector is estimated by solving a quadratic programming. The time-delays and the parameters are estimated according to the structure of the parameter estimation vector and the model equivalence principle, respectively. The proposed method is applicable even in the case of a few number of sampled data. The effectiveness of the proposed algorithm is verified by the numerical simulation results.https://ieeexplore.ieee.org/document/9015976/Closed-loop systembasis pursuit de-noisingsystem identificationtime-delay estimation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ying Chen Yanjun Liu Jing Chen Junxia Ma |
spellingShingle |
Ying Chen Yanjun Liu Jing Chen Junxia Ma A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising IEEE Access Closed-loop system basis pursuit de-noising system identification time-delay estimation |
author_facet |
Ying Chen Yanjun Liu Jing Chen Junxia Ma |
author_sort |
Ying Chen |
title |
A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising |
title_short |
A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising |
title_full |
A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising |
title_fullStr |
A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising |
title_full_unstemmed |
A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising |
title_sort |
novel identification method for a class of closed-loop systems based on basis pursuit de-noising |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
This paper presents a novel method to identify a class of closed-loop systems, in which both the forward channel and the feedback channel have unknown time-delays. Taking into account the time-delays, an overparameterized identification model with a sparse parameter vector is established. Based on the basis pursuit de-noising criterion, the sparse parameter vector is estimated by solving a quadratic programming. The time-delays and the parameters are estimated according to the structure of the parameter estimation vector and the model equivalence principle, respectively. The proposed method is applicable even in the case of a few number of sampled data. The effectiveness of the proposed algorithm is verified by the numerical simulation results. |
topic |
Closed-loop system basis pursuit de-noising system identification time-delay estimation |
url |
https://ieeexplore.ieee.org/document/9015976/ |
work_keys_str_mv |
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