Quantized Decentralized Adaptive Neural Network PI Tracking Control for Uncertain Interconnected Nonlinear Systems With Dynamic Uncertainties
DC Field | Value | Language |
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dc.contributor.author | Sun, Haibin | - |
dc.contributor.author | Zong, Guangdeng | - |
dc.contributor.author | Ahn, Choon Ki | - |
dc.date.accessioned | 2021-11-20T22:40:50Z | - |
dc.date.available | 2021-11-20T22:40:50Z | - |
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/128166 | - |
dc.description.abstract | In this paper, a decentralized adaptive neural network proportional-integral (PI) tracking control scheme is proposed for interconnected nonlinear systems with input quantization and dynamic uncertainties. This algorithm is underpinned by the use of the dynamic signal, graph theory, and function recombination to deal with the difficulties existing in the nontriangular form, unmodeled dynamics, and unknown interconnected terms. Recalling the backstepping method and neural network approximation technology, a new PI tracking controller characterized by simple structure and easy implementation is developed which ensures that all the closed-loop signals are uniformly ultimately bounded. The effectiveness of the obtained controller is exemplified via a numerical example and an application to an inverted pendulum. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Quantized Decentralized Adaptive Neural Network PI Tracking Control for Uncertain Interconnected Nonlinear Systems With Dynamic Uncertainties | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ahn, Choon Ki | - |
dc.identifier.doi | 10.1109/TSMC.2019.2918142 | - |
dc.identifier.scopusid | 2-s2.0-85104409421 | - |
dc.identifier.wosid | 000640749000040 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, v.51, no.5, pp.3111 - 3124 | - |
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 | 3111 | - |
dc.citation.endPage | 3124 | - |
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 | TIME-DELAY SYSTEMS | - |
dc.subject.keywordPlus | FEEDBACK-CONTROL | - |
dc.subject.keywordPlus | FUZZY CONTROL | - |
dc.subject.keywordPlus | STABILIZATION | - |
dc.subject.keywordPlus | DESIGN | - |
dc.subject.keywordPlus | REJECTION | - |
dc.subject.keywordPlus | SCHEME | - |
dc.subject.keywordAuthor | Quantization (signal) | - |
dc.subject.keywordAuthor | Uncertainty | - |
dc.subject.keywordAuthor | Neural networks | - |
dc.subject.keywordAuthor | Interconnected systems | - |
dc.subject.keywordAuthor | Nonlinear dynamical systems | - |
dc.subject.keywordAuthor | Control systems | - |
dc.subject.keywordAuthor | Decentralized control | - |
dc.subject.keywordAuthor | input quantization | - |
dc.subject.keywordAuthor | interconnected system | - |
dc.subject.keywordAuthor | neural network-based control | - |
dc.subject.keywordAuthor | nontriangular form | - |
dc.subject.keywordAuthor | proportional& | - |
dc.subject.keywordAuthor | #8211 | - |
dc.subject.keywordAuthor | integral (PI) tracking controller | - |
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