Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach
This paper presents a data-driven adaptive predictive control method using closed-loop subspace identification. As the predictor is the key element of the predictive controller, we propose to derive such predictor based on the subspace matrices which are obtained through the closed-loop subspace ide...
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Format: | Article |
Language: | English |
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Wiley
2014-01-01
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Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2014/869879 |
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author | Xiaosuo Luo Yongduan Song |
author_facet | Xiaosuo Luo Yongduan Song |
author_sort | Xiaosuo Luo |
collection | DOAJ |
description | This paper presents a data-driven adaptive predictive control method using closed-loop subspace identification. As the predictor is the key element of the predictive controller, we propose to derive such predictor based on the subspace matrices which are obtained through the closed-loop subspace identification algorithm driven by input-output data. Taking advantage of transformational system model, the closed-loop data is effectively processed in this subspace algorithm. By combining the merits of receding window and recursive identification methods, an adaptive mechanism for online updating subspace matrices is given. Further, the data inspection strategy is introduced to eliminate the negative impact of the harmful (or useless) data on the system performance. The problems of online excitation data inaccuracy and closed-loop identification in adaptive control are well solved in the proposed method. Simulation results show the efficiency of this method. |
format | Article |
id | doaj-art-19d5d756a4c4420a9bca830426e53e5e |
institution | Kabale University |
issn | 1085-3375 1687-0409 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
record_format | Article |
series | Abstract and Applied Analysis |
spelling | doaj-art-19d5d756a4c4420a9bca830426e53e5e2025-02-03T01:21:48ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/869879869879Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification ApproachXiaosuo Luo0Yongduan Song1School of Automation, Chongqing University, Chongqing 400044, ChinaSchool of Automation, Chongqing University, Chongqing 400044, ChinaThis paper presents a data-driven adaptive predictive control method using closed-loop subspace identification. As the predictor is the key element of the predictive controller, we propose to derive such predictor based on the subspace matrices which are obtained through the closed-loop subspace identification algorithm driven by input-output data. Taking advantage of transformational system model, the closed-loop data is effectively processed in this subspace algorithm. By combining the merits of receding window and recursive identification methods, an adaptive mechanism for online updating subspace matrices is given. Further, the data inspection strategy is introduced to eliminate the negative impact of the harmful (or useless) data on the system performance. The problems of online excitation data inaccuracy and closed-loop identification in adaptive control are well solved in the proposed method. Simulation results show the efficiency of this method.http://dx.doi.org/10.1155/2014/869879 |
spellingShingle | Xiaosuo Luo Yongduan Song Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach Abstract and Applied Analysis |
title | Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach |
title_full | Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach |
title_fullStr | Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach |
title_full_unstemmed | Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach |
title_short | Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach |
title_sort | adaptive predictive control a data driven closed loop subspace identification approach |
url | http://dx.doi.org/10.1155/2014/869879 |
work_keys_str_mv | AT xiaosuoluo adaptivepredictivecontroladatadrivenclosedloopsubspaceidentificationapproach AT yongduansong adaptivepredictivecontroladatadrivenclosedloopsubspaceidentificationapproach |