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Fuzzy Adaptive Swarm Control for the High-Order Self-organized System with Unknown Nonlinear Dynamics and Unmeasured States
Chen, Kang1; Xu, Tao2; Xu, Hao3; Chen, Long4
2022-02-01
Source PublicationInternational Journal of Fuzzy Systems
ISSN1562-2479
Volume24Issue:1Pages:391-404
Abstract

In the paper, we study the swarm control problem for a high-order self-organized system with unknown nonlinear dynamics and unmeasured states. In previous work, swarm control, which can change the distance between agents when swarm moves, is discussed. However, in practical applications, the high-order states of agents are not easy to be measured, and the unknown nonlinear dynamics in the system are also not conducive to the efficient and reliable operation of the system. To solve the problem that the high-order states of agents are not available when designing the controller, a high-gain state observer is designed to estimate those unmeasurable states. And to overcome the negative impact of unknown nonlinear dynamics on system performance, the fuzzy logic system is introduced to approximate the unknown nonlinear dynamics. Based on the sliding mode control theory, we design a distributed fuzzy adaptive swarm controller. And the stability of the proposed controller is proved. Finally, the self-organized system based on mecanum wheeled omnidirectional vehicles is taken as an example for numerical simulation, and the simulation results show that the proposed fuzzy adaptive swarm control law is effective.

KeywordFuzzy Logic Self-organized System Sliding Mode Control State Observer Swarm Control Unknown Nonlinear Dynamics Unmeasured States
DOI10.1007/s40815-021-01142-6
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS IDWOS:000675779600001
Scopus ID2-s2.0-85111121516
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorXu, Tao
Affiliation1.College of Astronautics, Northwestern Polytechnical University, Xi’an, China
2.Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, China
3.School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China
4.Department of Computer and Information Science, University of Macau, Macao
Recommended Citation
GB/T 7714
Chen, Kang,Xu, Tao,Xu, Hao,et al. Fuzzy Adaptive Swarm Control for the High-Order Self-organized System with Unknown Nonlinear Dynamics and Unmeasured States[J]. International Journal of Fuzzy Systems,2022,24(1):391-404.
APA Chen, Kang,Xu, Tao,Xu, Hao,&Chen, Long.(2022).Fuzzy Adaptive Swarm Control for the High-Order Self-organized System with Unknown Nonlinear Dynamics and Unmeasured States.International Journal of Fuzzy Systems,24(1),391-404.
MLA Chen, Kang,et al."Fuzzy Adaptive Swarm Control for the High-Order Self-organized System with Unknown Nonlinear Dynamics and Unmeasured States".International Journal of Fuzzy Systems 24.1(2022):391-404.
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