A Survey of An Intelligent Multi-Agent Formation Control

Chen, Qi-jie; Wang, Yao; Jin, Yuqiang; Wang, Taoyu; Nie, Xinhua; Yan, Tinglong

doi:10.3390/app13105934

Cited by 7 publications

(2 citation statements)

References 140 publications

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“…MAS formation and tracking control is considered a fundamental problem, in which agents are required to produce a desired trajectory. This topic has been extensively studied in the literature [6][7][8]. One of the most commonly proposed approaches for formation control in MASs is consensus protocols [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Consensus Tracking Control of Multiple Unmanned Aerial Vehicles Subject to Distinct Unknown Delays

Campos-Martínez,

Hernández-González,

Guerrero-Sánchez

et al. 2024

Machines

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This article deals with the consensus tracking problem for multi-agent systems (MAS) under the influence of unknown time-varying delays. Each agent of the MAS is a quadrotor unmanned aerial vehicle (UAV) represented as a linear continuous-time system. The main objective of this paper is the stabilization of multi-agent systems where the control input is affected by unknown time-varying delays, which are assumed to be upper-bounded, and where these bounds are not required to be known. The proposed observer-based control scheme guarantees the consensus tracking of multi-UAV systems with the desired H∞ performance, which adds a further level of mitigation of unknown delays present in MAS systems by minimizing the H∞ norm, which measures the maximum gain from the disturbance to the controlled output of the system. For each UAV agent, an unknown input observer is employed to isolate the unknown time-varying delays in the state estimation process. With the use of an unknown input observer-based consensus tracking control, sufficient conditions are derived to ensure that all follower UAVs can reach a consensus with the leader, despite the presence of distinct unknown time-varying delays. The stability of the proposed scheme is proven using Lyapunov theory for the leader and follower agents. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Consensus Tracking Control of Multiple Unmanned Aerial Vehicles Subject to Distinct Unknown Delays

Campos-Martínez,

Hernández-González,

Guerrero-Sánchez

et al. 2024

Machines

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show abstract

“…The multi-agent system has replaced human beings to perform specific complex tasks and has achieved remarkable results in intelligent scenarios. Multi-agent cooperation will have a higher value in the future and have excellent developmental prospects [1,2]. Facing complex environments, the multi-agent system needs to deal with agent disability, communication disconnection, and other emergencies to ensure the overall survivability of the system [3].…”

Section: Introductionmentioning

confidence: 99%

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

Zhang,

Chen,

Chen

et al. 2023

Applied Sciences

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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.

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A review of event-triggered consensus control in multi-agent systems

Dou,

Xing,

et al. 2024

Journal of Control and Decision

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A Survey of An Intelligent Multi-Agent Formation Control

Cited by 7 publications

References 140 publications

Consensus Tracking Control of Multiple Unmanned Aerial Vehicles Subject to Distinct Unknown Delays

Consensus Tracking Control of Multiple Unmanned Aerial Vehicles Subject to Distinct Unknown Delays

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

A review of event-triggered consensus control in multi-agent systems

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