Distributed dynamic obstacle avoidance design to connectivity-preserving formation control of uncertain underactuated surface vehicles under a directed network
DC Field | Value | Language |
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dc.contributor.author | Yoo, Sung Jin | - |
dc.contributor.author | Park, Bong Seok | - |
dc.date.accessioned | 2023-04-14T01:41:45Z | - |
dc.date.available | 2023-04-14T01:41:45Z | - |
dc.date.issued | 2023-04 | - |
dc.identifier.issn | 0029-8018 | - |
dc.identifier.issn | 1873-5258 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/66377 | - |
dc.description.abstract | This paper presents a Lyapunov-based recursive design approach for unifying distributed connectivity-preserving formation control and dynamic obstacle avoidance problems of uncertain multiple underactuated surface vehicles (USVs) with heterogeneous range constraints. Compared with related works, the main contribution of this study is to develop a novel control design for preserving network connectivity under dynamic obstacle avoidance in the distributed formation tracking framework. Because of the limited communication ranges, it is difficult to maintain the network interactions among USVs during dynamic obstacle avoidance. To deal with this problem, a collision-avoiding function is defined as a local error surface for the recursive control design, and a distributed complementary signal vector is introduced in the connectivity-preserving formation error surface. The complementary signals are designed to prevent network disconnections when the formation error is increased by the avoidance action and to ensure the stability of the collision-avoiding error dynamics, which eventually lead to preventing network disconnections during dynamic obstacle avoidance. An adaptive formation tracking scheme is designed via the neural networks-based command-filtered backstepping. The stability of the overall closed-loop system with preserved network connectivity and obstacle avoidance is proved based on the Lyapunov stability theorem. Finally, the theoretical approach is demonstrated through simulations. © 2023 Elsevier Ltd | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Elsevier Ltd | - |
dc.title | Distributed dynamic obstacle avoidance design to connectivity-preserving formation control of uncertain underactuated surface vehicles under a directed network | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.oceaneng.2023.113872 | - |
dc.identifier.bibliographicCitation | Ocean Engineering, v.273 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000944531000001 | - |
dc.identifier.scopusid | 2-s2.0-85148380042 | - |
dc.citation.title | Ocean Engineering | - |
dc.citation.volume | 273 | - |
dc.type.docType | Article | - |
dc.publisher.location | 영국 | - |
dc.subject.keywordAuthor | Dynamic obstacle avoidance | - |
dc.subject.keywordAuthor | Formation | - |
dc.subject.keywordAuthor | Lyapunov analysis | - |
dc.subject.keywordAuthor | Preserved network connectivity | - |
dc.subject.keywordAuthor | Underactuated surface vehicles (USVs) | - |
dc.subject.keywordPlus | ADAPTIVE NEURAL-CONTROL | - |
dc.subject.keywordPlus | SHIPS | - |
dc.subject.keywordPlus | TRACKING | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Oceanography | - |
dc.relation.journalWebOfScienceCategory | Engineering, Marine | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.relation.journalWebOfScienceCategory | Engineering, Ocean | - |
dc.relation.journalWebOfScienceCategory | Oceanography | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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