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Novoth, S, Zhang, Q, Ji, K and Yu, DL (2020) Distributed Formation Control for Multi-Vehicle Systems With Splitting and Merging Capability. IEEE Control Systems Letters, 5 (1). pp. 355-360. ISSN 2475-1456
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Abstract
This letter develops a novel strategy for splitting and merging of agents travelling in formation. The method converts the formation control problem into an optimization problem, which is solved among the agents in a distributed fashion. The proposed control strategy is one type of Distributed Model Predictive Control (DMPC) which allows the system to cope with disturbances and dynamic environments. A modified Alternating Direction Method of Multipliers (ADMM) is designed to solve the trajectory optimization problem and achieve formation scaling. Furthermore, a mechanism is designed to implement path homotopy in splitting and merging of the formation, which examines the H-signature of the generated trajectories. Simulation shows that, by using the proposed method, the formation is able to automatically resize and dynamically split to better avoid obstacles, even in the case of losing communication among agents. Upon splitting the newly formed groups proceed and merge again when it becomes possible.
| Item Type: | Article |
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| Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics. Nuclear engineering |
| Divisions: | Electronics & Electrical Engineering (merged with Engineering 10 Aug 20) |
| Publisher: | IEEE |
| Date Deposited: | 03 Jul 2020 09:37 |
| Last Modified: | 04 Sep 2021 07:03 |
| DOI or ID number: | 10.1109/LCSYS.2020.3002218 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/13243 |
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