Consensus-based cooperative formation control with collision avoidance for a multi-UAV system

Kuriki, Yasuhiro; Namerikawa, Toru

doi:10.1109/acc.2014.6858777

Cited by 183 publications

(79 citation statements)

References 20 publications

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“…Over the past few years, distributed cooperative control of multi-agent systems has gained a surge of interest due to its great potential applications in many scientific and engineering fields including flocking, formation flying of unmanned air vehicles, cooperative manipulation of multiple robots [1][2][3], and so forth. Among the above research works, consensus problem is a fundamental issue because it is the premise for many cooperative tasks.…”

Section: Introductionmentioning

confidence: 99%

Distributed adaptive output feedback consensus tracking for multi-agent systems with unknown nonlinearities

Sun

Zhang

2015

2015 34th Chinese Control Conference (CCC)

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This paper considers the distributed consensus tracking problem for multi-agent systems with unknown nonlinearities in the followers. Based on parameterizing the nonlinearities of all followers, distributed adaptive consensus protocols with dynamic coupling gains are designed with the relative output information which are more practical than the state-feedback ones. The protocols guarantee that the consensus tracking errors converge to a small neighborhood around the origin and all the signals in the closed-loop dynamics are uniformly ultimately bounded. The dynamic coupling gains are updated without knowing the eigenvalues of the Laplacian matrix which is actually the global information. Finally, the theoretical results are illustrated through an example.

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Section: Introductionmentioning

confidence: 99%

Distributed adaptive output feedback consensus tracking for multi-agent systems with unknown nonlinearities

Sun

Zhang

2015

2015 34th Chinese Control Conference (CCC)

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“…We have been studying cooperative control problems for multi-vehicle systems [6]- [9] with particular focus on solving formation control problems using a consensus algorithm. We expressed the UAV dynamics on the horizontal plane as a fourth-order system and the dynamics in the vertical direction as a second-order system separately, then proposed two consensus-based control algorithms for a multi-UAV system to cooperatively fly in formation on the horizontal plane and in the vertical direction [8], [9]. Using these two consensusbased cooperative control algorithms, UAVs can fly in formation in three-dimensional space.…”

Section: Introductionmentioning

confidence: 99%

Experimental validation of cooperative formation control with collision avoidance for a multi-UAV system

Kuriki

Namerikawa

2015

2015 6th International Conference on Automation, Robotics and Applications (ICARA)

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In this study, we consider cooperative control issues for a multi-unmanned aerial vehicle (UAV) system. Specifically, we present a cooperative formation control strategy for a multi-UAV system with unidirectional network links. Our strategy is to apply a consensus-based algorithm and leaderfollower structure to the UAVs so that they can cooperatively fly in formation. The leader provides each UAV with commands to generate a geometric configuration of the formation. Convergence is guaranteed when the cooperative formation control algorithm is applied to the UAVs. Collisions among UAVs can occur when they are flying with the cooperative control UAVs. Our strategy for collision avoidance is to apply an artificial potential approach to the UAVs. Experiments are performed on multiple commercial small UAVs to validate the proposed formation control algorithm with collision-avoidance capability.

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“…The application areas of multiagent systems are very extensive, e.g. robotics [1], [2], unmanned aerial vehicles [3], space systems [4], autonomous underwater vehicles [5], and so on.…”

Section: Introductionmentioning

confidence: 99%

Output synchronization of multi-agent systems with nonlinear non-minimum phase dynamics

Shamsi

Talebi

Abdollahi

2015

2015 American Control Conference (ACC)

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This paper deals with output synchronization problem in nonlinear multi-agent systems. The main contribution of the paper is to guarantee output synchronization in the network while the dynamics of agents exhibit nonminimum phase behavior. To achieve this goal, a control signal is presented for each agent consisting of two terms. The first term is a linear function of each agent states employed in order to overcome the non-minimum phase dynamics of the multiagent system, whereas the second term is a function of the output of neighboring agents which provides coupling among agents and guarantees output synchronization in the network. A numerical example is presented to verify the effectiveness of the proposed approach.

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Consensus-based cooperative formation control with collision avoidance for a multi-UAV system

Cited by 183 publications

References 20 publications

Distributed adaptive output feedback consensus tracking for multi-agent systems with unknown nonlinearities

Distributed adaptive output feedback consensus tracking for multi-agent systems with unknown nonlinearities

Experimental validation of cooperative formation control with collision avoidance for a multi-UAV system

Output synchronization of multi-agent systems with nonlinear non-minimum phase dynamics

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