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오태훈

Oh, Tae Hoon
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dc.citation.endPage 33 -
dc.citation.startPage 25 -
dc.citation.title JOURNAL OF PROCESS CONTROL -
dc.citation.volume 116 -
dc.contributor.author Oh, Tae Hoon -
dc.contributor.author Kim, Jong Woo -
dc.contributor.author Son, Sang Hwan -
dc.contributor.author Jeong, Dong Hwi -
dc.contributor.author Lee, Jong Min -
dc.date.accessioned 2024-03-13T10:05:12Z -
dc.date.available 2024-03-13T10:05:12Z -
dc.date.created 2024-03-13 -
dc.date.issued 2022-08 -
dc.description.abstract This paper proposes a multi-strategy control scheme, which modifies the optimal control problem of robust model predictive control (RMPC) to reduce the on-line computational load or extend the feasible region. The proposed controller is designed to stabilize the system with respect to a subset of the disturbance set. If the disturbance is realized from the rest of the subset, another control strategy is automatically involved to keep the state inside the pre-determined bounded set. The existence of this pre-determined set is proven, and an efficient algorithm is proposed to generate this set. In addition, it is shown that the recursive feasibility and stability of the original RMPC is sustained for the proposed controller. This implies that the proposed method can be applied to a wide range of existing RMPC. Three illustrative examples describe the fundamental ideas and practical advantages. (c) 2022 Elsevier Ltd. All rights reserved. -
dc.identifier.bibliographicCitation JOURNAL OF PROCESS CONTROL, v.116, pp.25 - 33 -
dc.identifier.doi 10.1016/j.jprocont.2022.05.011 -
dc.identifier.issn 0959-1524 -
dc.identifier.scopusid 2-s2.0-85131452890 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/81574 -
dc.identifier.wosid 000822930300003 -
dc.language 영어 -
dc.publisher ELSEVIER SCI LTD -
dc.title Multi-strategy control to extend the feasibility region for robust model predictive control -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Automation & Control Systems; Engineering, Chemical -
dc.relation.journalResearchArea Automation & Control Systems; Engineering -
dc.type.docType Article; Early Access -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Robust control -
dc.subject.keywordAuthor Model predictive control -
dc.subject.keywordAuthor Uncertain systems -
dc.subject.keywordAuthor Stability -
dc.subject.keywordPlus OPTIMIZATION -
dc.subject.keywordPlus UNCERTAINTY -
dc.subject.keywordPlus ALGORITHM -
dc.subject.keywordPlus SETS -
dc.subject.keywordPlus MPC -

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