3D Multi‐Agent Formation Control with Rigid Body Maneuvers

Zhang, Pengpeng; Queiroz, M.S. de

doi:10.1002/asjc.1814

Cited by 20 publications

(15 citation statements)

References 37 publications

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“…Following is the main result of this paper: Theorem 1. Given system of N agents of (2)(3) with control input of u i (t) given by (8), auxiliary state dynamics given by ( 6) (7) where the communication graph (t) is directed leader-follower where ∈ Z N is the leader node, reference-output i,re (t) given by (5), and dynamic compensator given by (9). Further, let d be the desired scaling factor of the formation.…”

Section: The Proposed Control Inputmentioning

confidence: 99%

“…In recent years, the problem of cooperative control of MASs have received great attention from the research community. Problems studied in cooperative control of MASs include but not limited to consensus or synchronization where the objective is to reach agreement among agents [1][2][3][4], containment control where the objective is such that the states of agents asymptotically converge to the convex hull of the leader agents' states [5][6][7], and multi-agent formation where the objective is such that asymptotically agents' states or output differs by a predefined vector or desired formation pattern [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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Scalable Formation of Heterogeneous Agents considering Unknown Disturbances

Djamari

2020

Asian Journal of Control

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The problem considered in this work is formation control of linear heterogeneous Multi-Agent Systems (MASs) where the size of the formation is scalable via a scaling factor determined by a leader agent. Agents are communicating through a leader-follower time-varying network and they are subjected to an unknown disturbances. Past works on scalable formation are limited to the case of homogeneous agents under fixed communication network and without considering disturbances. The control law in this work is based on the internal model principle and the H ∞ control theory. A dynamic compensator is designed based on the regular H ∞ output feedback problem and its output is used as the feedback signal in the main control input. Meanwhile, the main control input is designed based on the internal model principle. It is shown that the effect of the disturbance to the agent's output is minimized and the tracking error satisfies H ∞ performance. The effectiveness of the proposed method is shown by numerical examples.

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Section: The Proposed Control Inputmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scalable Formation of Heterogeneous Agents considering Unknown Disturbances

Djamari

2020

Asian Journal of Control

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“…where 3 . It can be seen that the nonlinear time-varying uncertain- In this example, Figure 6 shows that the consensus tracking is achieved in two seconds.…”

Section: Figurementioning

confidence: 99%

“…Cooperative control of multi-agent systems (MASs) is an emerging research direction and leads to many results such as formation control [1][2][3][4][5], flocking [6,7], data fusion [8,9] and so on. Consensus is the basic problem of cooperative control.…”

Section: Introductionmentioning

confidence: 99%

Robust distributed consensus tracking control for high‐order uncertain nonlinear MASs with directed topologies

Liu

Yao

Wang

et al. 2019

Asian Journal of Control

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This paper addresses the robust distributed consensus tracking problem for leader-follower multi-agent systems (MASs) with nonlinear dynamics and external disturbances under directed graph topologies. The nonlinear uncertainties are not required to be continuous or meet the matching conditions. The backstepping design method combined with signal compensation approach is proposed to design robust controllers in order to guarantee the consensus tracking property between the followers and the one leader. Moreover, the dynamic surface control technique is used to deal with the 'explosion of complexity' problem. It is proven that the robust distributed consensus tracking property of the MASs can be guaranteed. Furthermore, the consensus tracking errors can be designed as small as required and the convergence speed can be chosen arbitrarily. Finally, two examples are presented to show the validity of the proposed consensus tracking control protocols.

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“…Consider the behavior-based strategy where the weighted average of each aircraft and the chosen route control the movement of every UAV [11]. For the virtual formation, the formation configuration is considered a rigid body, and the dynamics of the virtual leader UAV guide every follower to maintain the fixed virtual configuration [12,13]. e drawback of the virtual formation is that its operation is more central; i.e., a single aircraft malfunction can disrupt the entire formation [14].…”

Section: Introductionmentioning

confidence: 99%

A Leader‐Follower Formation Control of Multi‐UAVs via an Adaptive Hybrid Controller

et al. 2021

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The purpose of this study is to offer an adaptive hybrid controller for the formation control of multiple unmanned aerial vehicles (UAVs) leader-follower configurations with communication delay. Although numerous studies about the control of the formation exist, very few incorporate the delay in their model and are adaptive as well. The motivation behind this article is to bridge that gap. The strategy consists of an adaptive fuzzy logic controller and a Proportional, Integral, and Derivative (PID) controller where the logic controller fines/tunes the PID controller gains. The controller also consists of an integrator that raises the order of the system which helps reduce the noise and steady-state errors. The simulations confirm that the proposed technique is robust and satisfies mission requirements. Moreover, the flying formations of the swarm were created by a B-spline curve based on a simple waypoint. The main contribution of this study is to present a model where the formation remains stable during the whole flight, errors are within the optimal range, and the time delays are manageable.

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3D Multi‐Agent Formation Control with Rigid Body Maneuvers

Cited by 20 publications

References 37 publications

Scalable Formation of Heterogeneous Agents considering Unknown Disturbances

Scalable Formation of Heterogeneous Agents considering Unknown Disturbances

Robust distributed consensus tracking control for high‐order uncertain nonlinear MASs with directed topologies

A Leader‐Follower Formation Control of Multi‐UAVs via an Adaptive Hybrid Controller

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