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Distributed Optimal Solutions for Multiagent Pursuit-Evasion Games
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
The Chinese University of Hong Kong, Department of Mechanical and Automation Engineering, Shatin, N.T, Hong Kong, Shatin, N.T.
2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 6424-6429Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all players desire to maintain cohesion with their teammates. The goals of agents are obviously reflected in the obtained optimal control strategies which consist of an attracting term and/or a repelling term. Nash equilibrium is obtained by means of optimal strategies using the solutions of the HJI equations. Furthermore, three scenarios are considered in the MPE game: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple-pursuer-multiple-evader, where sufficient conditions are given for pursuers in achieving capture or formation control with ultimate zero or bounded errors. It is shown that the conditions depend on the structure of the communication graph, the parameters in the controllers, and the expected formation configurations. Finally, both simulations and real flight experiments successfully demonstrate the effectiveness of the proposed strategies.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 6424-6429
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-343712DOI: 10.1109/CDC49753.2023.10383808ISI: 001166433805043Scopus ID: 2-s2.0-85184811317OAI: oai:DiVA.org:kth-343712DiVA, id: diva2:1839907
Conference
62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, Dec 13 2023 - Dec 15 2023
Note

Part of proceedings ISBN 9798350301243

QC 20240222

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-04-04Bibliographically approved

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Zhou, Panpan

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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  • de-DE
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Output format
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