Offset Free Tracking Predictive Control Based on Dynamic PLS Framework
This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS) framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-10-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/8/4/121 |
| _version_ | 1828768589504577536 |
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| author | Jin Xin Wang Yue Luo Lin |
| author_facet | Jin Xin Wang Yue Luo Lin |
| author_sort | Jin Xin |
| collection | DOAJ |
| description | This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS) framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC) controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method. |
| first_indexed | 2024-12-11T13:32:32Z |
| format | Article |
| id | doaj.art-043f0aea7cb34e2985ac3ebe4b92d968 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-11T13:32:32Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-043f0aea7cb34e2985ac3ebe4b92d9682022-12-22T01:05:11ZengMDPI AGInformation2078-24892017-10-018412110.3390/info8040121info8040121Offset Free Tracking Predictive Control Based on Dynamic PLS FrameworkJin Xin0Wang Yue1Luo Lin2School of Information and Control Engineering, Liaoning Shihua University, Fushun 113001, ChinaSchool of Information and Control Engineering, Liaoning Shihua University, Fushun 113001, ChinaSchool of Information and Control Engineering, Liaoning Shihua University, Fushun 113001, ChinaThis paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS) framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC) controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.https://www.mdpi.com/2078-2489/8/4/121partial least squaremodel predictive controloffset free controldistributed controller |
| spellingShingle | Jin Xin Wang Yue Luo Lin Offset Free Tracking Predictive Control Based on Dynamic PLS Framework Information partial least square model predictive control offset free control distributed controller |
| title | Offset Free Tracking Predictive Control Based on Dynamic PLS Framework |
| title_full | Offset Free Tracking Predictive Control Based on Dynamic PLS Framework |
| title_fullStr | Offset Free Tracking Predictive Control Based on Dynamic PLS Framework |
| title_full_unstemmed | Offset Free Tracking Predictive Control Based on Dynamic PLS Framework |
| title_short | Offset Free Tracking Predictive Control Based on Dynamic PLS Framework |
| title_sort | offset free tracking predictive control based on dynamic pls framework |
| topic | partial least square model predictive control offset free control distributed controller |
| url | https://www.mdpi.com/2078-2489/8/4/121 |
| work_keys_str_mv | AT jinxin offsetfreetrackingpredictivecontrolbasedondynamicplsframework AT wangyue offsetfreetrackingpredictivecontrolbasedondynamicplsframework AT luolin offsetfreetrackingpredictivecontrolbasedondynamicplsframework |