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Distributed adaptive optimization-based formation tracking with double parameter projections for multi-agent systems

delete2022-07-01
delete7
PRE
AI
彭朝霞 (Zhaoxia Peng)
B
Bofan Wu *
闻国光 (Guoguang Wen)
S
Shichun Yang
T
Tingwen Huang
DOI:10.1016/j.jfranklin.2022.05.041delete
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Abstract

Abstract

En 中文
In this paper, a distributed adaptive optimization-based formation tracking strategy with double parameter projections for multi-agent systems is addressed under a centralized task allocation and distributed task execution (CTA-DTE) framework. Since a pre-described formation strategy is unable to adapt to a complex and dynamic environment, an optimization-based approach is proposed to transfer the formation tracking problem into a time-varying optimization one, subject to some constraints with several time-varying parameters which determine the rule of formation configuration change adaptively. These parameters are computed by a centralized unit and allocated to each agent as a global mission. Furthermore, each agent cooperates with others to execute this mission under a distributed optimization-based strategy, which combines a geometric center observer technology and a novel double parameter projections technology. The former ensures accurate tracking of a continuous reference trajectory. The latter guarantees that all agents enter into a time-varying security region and never escape from it, and meanwhile, all agents are attracted towards the best time-varying formation configuration via a gradient descent with a compensation. Finally, some simulation results are illustrated to verify the effectiveness of the strategy. (c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Keywords:
VARYING FORMATION TRACKING
PREDICTIVE CONTROL
AVOIDANCE

Journal

J
Journal of the Franklin Institute-Engineering and Applied Mathematics
IF:
3.7
Papers:
6.4K
Citations:
1.5W

Organization

B
Beijing Jiaotong University
Scholars:
2.2W
Papers: 1.7W
Citations: 1.2W
B
Beihang University
Scholars:
5.2W
Papers: 4.1W
Citations: 37
Q
qatar foundation (qf)
Scholars:
6.3K
Papers: 7.0K
Citations: 8
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