Residential College | false |
Status | 已發表Published |
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 Publication | International Journal of Fuzzy Systems |
ISSN | 1562-2479 |
Volume | 24Issue: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. |
Keyword | Self-organized System Unknown Nonlinear Dynamics Unmeasured States Sliding Mode Control Swarm Control State Observer Fuzzy Logic |
DOI | 10.1007/s40815-021-01142-6 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Automation & Control Systems ; Computer Science |
WOS Subject | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Information Systems |
WOS ID | WOS:000675779600001 |
Publisher | SPRINGER HEIDELBERG, TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY |
Scopus ID | 2-s2.0-85111121516 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Corresponding Author | Xu, Tao |
Affiliation | 1.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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