Neural-Based Decentralized Adaptive Finite-Time Control for Nonlinear Large-Scale Systems With Time-Varying Output Constraints
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Du, Peihao | - |
dc.contributor.author | Liang, Hongjing | - |
dc.contributor.author | Zhao, Shiyi | - |
dc.contributor.author | Ahn, Choon Ki | - |
dc.date.accessioned | 2021-11-20T03:40:56Z | - |
dc.date.available | 2021-11-20T03:40:56Z | - |
dc.date.created | 2021-08-30 | - |
dc.date.issued | 2021-05 | - |
dc.identifier.issn | 2168-2216 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/128071 | - |
dc.description.abstract | This paper addresses the adaptive finite-time decentralized control problem for time-varying output-constrained nonlinear large-scale systems preceded by input saturation. The intermediate control functions designed are approximated by neural networks. Time-varying barrier Lyapunov functions are used to ensure that the system output constraints are never breached. An adaptive finite-time decentralized control scheme is devised by combining the backstepping approach with Lyapunov function theory. Under the action of the proposed approach, the system stability and desired control performance can be obtained in finite time. The feasibility of this control strategy is demonstrated by using simulation results. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Neural-Based Decentralized Adaptive Finite-Time Control for Nonlinear Large-Scale Systems With Time-Varying Output Constraints | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ahn, Choon Ki | - |
dc.identifier.doi | 10.1109/TSMC.2019.2918351 | - |
dc.identifier.scopusid | 2-s2.0-85104490740 | - |
dc.identifier.wosid | 000640749000042 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, v.51, no.5, pp.3136 - 3147 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | - |
dc.citation.title | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | - |
dc.citation.volume | 51 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 3136 | - |
dc.citation.endPage | 3147 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Cybernetics | - |
dc.subject.keywordPlus | TRACKING CONTROL | - |
dc.subject.keywordPlus | NETWORK CONTROL | - |
dc.subject.keywordPlus | STABILIZATION | - |
dc.subject.keywordAuthor | Time-varying systems | - |
dc.subject.keywordAuthor | Nonlinear systems | - |
dc.subject.keywordAuthor | Adaptive systems | - |
dc.subject.keywordAuthor | Large-scale systems | - |
dc.subject.keywordAuthor | Stability analysis | - |
dc.subject.keywordAuthor | Artificial neural networks | - |
dc.subject.keywordAuthor | Lyapunov methods | - |
dc.subject.keywordAuthor | Finite time | - |
dc.subject.keywordAuthor | input saturation | - |
dc.subject.keywordAuthor | neural network (NN) | - |
dc.subject.keywordAuthor | nonlinear large-scale systems | - |
dc.subject.keywordAuthor | time-varying output constraints | - |
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