Neural-Network Approximation-Based Adaptive Periodic Event-Triggered Output-Feedback Control of Switched Nonlinear Systems
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Li, Shi | - |
dc.contributor.author | Ahn, Choon Ki | - |
dc.contributor.author | Guo, Jian | - |
dc.contributor.author | Xiang, Zhengrong | - |
dc.date.accessioned | 2022-02-26T06:41:02Z | - |
dc.date.available | 2022-02-26T06:41:02Z | - |
dc.date.created | 2022-02-07 | - |
dc.date.issued | 2021-08 | - |
dc.identifier.issn | 2168-2267 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/136973 | - |
dc.description.abstract | This study considers an adaptive neural-network (NN) periodic event-triggered control (PETC) problem for switched nonlinear systems (SNSs). In the system, only the system output is available at sampling instants. A novel adaptive law and a state observer are constructed by using only the sampled system output. A new output-feedback adaptive NN PETC strategy is developed to reduce the usage of communication resources; it includes a controller that only uses event-sampling information and an event-triggering mechanism (ETM) that is only intermittently monitored at sampling instants. The proposed adaptive NN PETC strategy does not need restrictions on nonlinear functions reported in some previous studies. It is proven that all states of the closed-loop system (CLS) are semiglobally uniformly ultimately bounded (SGUUB) under arbitrary switchings by choosing an allowable sampling period. Finally, the proposed scheme is applied to a continuous stirred tank reactor (CSTR) system and a numerical example to verify its effectiveness. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | PRESCRIBED PERFORMANCE | - |
dc.subject | GLOBAL STABILIZATION | - |
dc.subject | TRACKING CONTROL | - |
dc.subject | DESIGN | - |
dc.title | Neural-Network Approximation-Based Adaptive Periodic Event-Triggered Output-Feedback Control of Switched Nonlinear Systems | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ahn, Choon Ki | - |
dc.identifier.doi | 10.1109/TCYB.2020.3022270 | - |
dc.identifier.scopusid | 2-s2.0-85112729285 | - |
dc.identifier.wosid | 000681200300016 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON CYBERNETICS, v.51, no.8, pp.4011 - 4020 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON CYBERNETICS | - |
dc.citation.title | IEEE TRANSACTIONS ON CYBERNETICS | - |
dc.citation.volume | 51 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 4011 | - |
dc.citation.endPage | 4020 | - |
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, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Cybernetics | - |
dc.subject.keywordPlus | DESIGN | - |
dc.subject.keywordPlus | GLOBAL STABILIZATION | - |
dc.subject.keywordPlus | PRESCRIBED PERFORMANCE | - |
dc.subject.keywordPlus | TRACKING CONTROL | - |
dc.subject.keywordAuthor | Adaptive neural-network (NN) control | - |
dc.subject.keywordAuthor | Adaptive systems | - |
dc.subject.keywordAuthor | Artificial neural networks | - |
dc.subject.keywordAuthor | Nonlinear systems | - |
dc.subject.keywordAuthor | Observers | - |
dc.subject.keywordAuthor | Switched systems | - |
dc.subject.keywordAuthor | Switches | - |
dc.subject.keywordAuthor | output feedback | - |
dc.subject.keywordAuthor | periodic event-triggered control (PETC) | - |
dc.subject.keywordAuthor | switched nonlinear system (SNS) | - |
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