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Research Papers

Leader–Follower Consensus Control of Multiple Quadcopters Under Communication Delays

[+] Author and Article Information
Zipeng Huang

Department of Mechanical Engineering,
Dalhousie University,
Halifax, NS B3H 4R2, Canada
e-mail: Zipeng.Huang@Dal.Ca

Ya-Jun Pan

Department of Mechanical Engineering,
Dalhousie University,
Halifax, NS B3H 4R2, Canada
e-mail: Yajun.Pan@Dal.Ca

Robert Bauer

Department of Mechanical Engineering,
Dalhousie University,
Halifax, NS B3H 4R2, Canada
e-mail: Robert.Bauer@Dal.Ca

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received August 6, 2018; final manuscript received May 14, 2019; published online June 10, 2019. Assoc. Editor: Inna Sharf.

J. Dyn. Sys., Meas., Control 141(10), 101006 (Jun 10, 2019) (10 pages) Paper No: DS-18-1361; doi: 10.1115/1.4043802 History: Received August 06, 2018; Revised May 14, 2019

This paper develops a novel decentralized leader–follower consensus algorithm for multiple-quadcopter systems under uniform constant and asynchronous time-varying communication delays. The consensus problem is formulated as the stability analysis and static controller design problem of a delayed system by defining the consensus error dynamics. Lyapunov-based methods along with the linear matrix inequality (LMI) techniques are utilized to derive the sufficient conditions for the control gain design that ensure asymptotic consensusability in the constant delay case, and consensus with bounded errors in the time-varying delay case. Also the computational complexity of solving control gains can be significantly reduced by decomposing the sufficient conditions into a set of equivalent low-dimensional conditions under undirected communication topologies. Simulation results show that larger systems are generally more susceptible to communication delays, and systems are more robust to delays when more followers are directly connected to the leader.

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Figures

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Fig. 1

Communication topologies (a)–(h)

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Fig. 2

Position profile of the system under communication topology (e) and τ=0.5 s

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Fig. 3

Ring type communication topology with N agents

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Fig. 4

Position profile of the six-agents system under constant delay τ=0.3 s

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Fig. 5

Maximum allowable delay versus θ1 and θ2

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Fig. 6

Consensus time versus θ1 and θ2

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Fig. 7

Delay signals within communication channels to agent two

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Fig. 8

Feasibility region of the controller with respect to γ ands

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Fig. 9

Consensus error under controllers designed based on Eqs. (18) and (26)

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Fig. 10

Position response when t≤150 s

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Fig. 11

Position response when t≤25 s

Tables

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