Time-Varying Topology Formation Reconfiguration Control of the Multi-Agent System Based on the Improved Hungarian Algorithm

Author:

Zhang Yingxue1,Chen Meng12,Chen Jinbao1,Chen Chuanzhi1,Yu Hongzhi1,Zhang Yunxiao1,Deng Xiaokang1

Affiliation:

1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

2. Shanghai Key Laboratory of Spacecraft Mechanism, Shanghai 201109, China

Abstract

Distributed time-varying formation technology for multi-agent systems is recently become a research hotspot in formation control field. However, the formation reconfiguration control technology for agents that randomly appeared to fail during maneuvers is rarely studied. In this paper, the topological relations between intelligence are designed by graph theory to simplify the cooperative interaction between multi-agent systems. Moreover, this paper constructs the time-varying configuration of the target formation based on the rigidity graph theory and leader–follower strategy. Drawing on the establishment of the expert experience database in a collaborative process, we innovatively propose the establishment of a graphic library to help the multi-agent system quickly form an affine transformation as soon as it is disabled. Secondly, the improved Hungarian algorithm is adopted to allocate the target point when the first failure occurs. This algorithm incorporates a gradient weighting factor from the auction algorithm to improve the speed of system reconfiguration with minimum path cost. On this basis, a distributed multi-agent control law based on consistency theory is established, and the system’s stability can be guaranteed via Lyapunov functions. Finally, the simulation results demonstrate the feasibility and effectiveness of the proposed formation reconfiguration control algorithm in a collaborative environment.

Funder

National Natural Science Foundation of China

Interdisciplinary Innovation Fund for Doctoral Students of Nanjing University of Aeronautics and Astronautics

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference25 articles.

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5. Thuy, N., Bui, D., and Phung, M. (2022, January 21–24). Deployment of UAVs for Optimal Multihop Ad-hoc Networks Using Particle Swarm Optimization and Behavior-based Control. Proceedings of the International Conference on Control, Automation and Information Sciences (ICCAIS), Hanoi, Vietnam.

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