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Leader-follower Multi-Robot Formation System Using Model Predictive Control Method Based on Particle Swarm Optimization
Xiao, Hanzhen; Chen, C. L. Philip; IEEE
2017
Conference Name2017 32ND YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC)
Pages480-484
Conference Date19 May 2017through 21 May 2017
Conference PlaceHefei
Publication Place345 E 47TH ST, NEW YORK, NY 10017 USA
PublisherIEEE
Abstract

For controlling the multi-robot formation system, a leader-follower separation-bearing-orientation scheme (SBOS) is proposed and the leader-follower relationship can be represented as a formation-error kinematic system through SBOS strategy. In order to achieve the control objective, a nonlinear model predictive control (NMPC) strategy is applied to formulate the formation-error kinematic into a minimization optimization problem according to cost function. To solve this optimization problem online efficiently, a particle swarm optimization (PSO) is proposed to search for the global optimal solution as the control input. In the end of this work, simulations of the multi-robot formation are performed to verify the effectiveness of the developed strategy.

KeywordMultiple Mobile Robots Formation Separation-bearing-orientation Scheme (Sbos) Nonlinear Model Predictive Control (Nmpc) Particle Swarm Optimization (Pso)
DOI10.1109/YAC.2017.7967457
URLView the original
Language英語English
WOS Research AreaAutomation & Control Systems
WOS SubjectAutomation & Control Systems
WOS IDWOS:000425862800090
The Source to ArticleWOS
Scopus ID2-s2.0-85026877068
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Citation statistics
Document TypeConference paper
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Xiao, Hanzhen,Chen, C. L. Philip,IEEE. Leader-follower Multi-Robot Formation System Using Model Predictive Control Method Based on Particle Swarm Optimization[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017, 480-484.
APA Xiao, Hanzhen., Chen, C. L. Philip., & IEEE (2017). Leader-follower Multi-Robot Formation System Using Model Predictive Control Method Based on Particle Swarm Optimization. , 480-484.
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