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Technical Brief

# Consensus-Based Cooperative Formation Control for Multiquadcopter System With Unidirectional Network Connections

[+] Author and Article Information
Toru Namerikawa

Department of Integrated Design Engineering,
Graduate School of Science and Technology,
Keio University,
Yokohama 223-8522, Japan
e-mail: namerikawa@sd.keio.ac.jp

Yasuhiro Kuriki

Department of Integrated Design Engineering,
Graduate School of Science and Technology,
Keio University,
Yokohama 223-8522, Japan
e-mail: yasuhiro@nl.sd.keio.ac.jp

Ahmed Khalifa

Department of Industrial Electronics and
Control Engineering,
Faculty of Electronic Engineering,
Menoufia University,
Menoufia 32952, Egypt
e-mail: ahmed.khalifa@el-eng.menofia.edu.eg

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 2, 2016; final manuscript received October 19, 2017; published online December 14, 2017. Assoc. Editor: Dejan Milutinovic.

J. Dyn. Sys., Meas., Control 140(4), 044502 (Dec 14, 2017) (8 pages) Paper No: DS-16-1224; doi: 10.1115/1.4038375 History: Received May 02, 2016; Revised October 19, 2017

## Abstract

In this paper, we consider cooperative control issues for a multi-unmanned aerial vehicle (UAV) system. We propose a cooperative formation control strategy with unidirectional network connections between UAVs. Our strategy is to apply a consensus-based algorithm to the UAVs so that they can cooperatively fly in formation. First, we show that UAV models on the horizontal plane and in the vertical direction are expressed as a fourth- and second-order system, respectively. Then, we show that the stability discriminants of the multi-UAV system on the horizontal plane and in the vertical direction are expressed as polynomials. For a network structure composed of bidirectional or unidirectional network connections under the assumption that the network has a directed spanning tree, we provide conditions for formation control gains such that all roots of the polynomials have negative real parts in order for the UAVs to asymptotically converge to the positions for a desired formation by using the generalized Routh stability criterion. The proposed control algorithms are validated through simulations, and experiments are performed on multiple commercial small UAVs to validate the proposed control algorithm.

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## References

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## Figures

Fig. 1

Desired formation for three UAVs and leader

Fig. 2

Network structure for simulations and experimental validation

Fig. 3

AR.Drone: control structure

Fig. 4

Trajectory on horizontal plane using formation control algorithm (7) with control gains for convergence (case I)

Fig. 5

Difference from the desired positions on horizontal plane using formation control algorithm (7) with control gains for convergence (case I)

Fig. 6

Trajectory on horizontal plane using formation control algorithm (7) with control gains for divergence (case II)

Fig. 7

Difference from the desired positions on horizontal plane using formation control algorithm (7) with control gains for divergence (case II)

Fig. 8

Simulation results in vertical direction using formation control algorithm (28) with control gains for divergence (case II)

Fig. 9

Simulation and experimental results in vertical direction using formation control algorithm (28) with control gains for convergence (case I)

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