Distributed backstepping based control of multiple UAV formation flight subject to time delays
In this study, the authors propose a backstepping-based, distributed formation control method that is stable independent of time delays in communication among multiple unmanned aerial vehicles (UAVs). Centralised formation control of UAVs requires each agent to maintain a separation distance from ot...
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Published in | IET control theory & applications Vol. 14; no. 12; pp. 1628 - 1638 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
The Institution of Engineering and Technology
13.08.2020
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Subjects | |
Online Access | Get full text |
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Summary: | In this study, the authors propose a backstepping-based, distributed formation control method that is stable independent of time delays in communication among multiple unmanned aerial vehicles (UAVs). Centralised formation control of UAVs requires each agent to maintain a separation distance from other agents, which burdens the communication network of the UAVs. To overcome this problem, the authors consider a distributed control scheme wherein each agent updates its attitude and position based on the state information gathered through its neighbours. Instead of directly controlling the thrust generated by the propellers, they partition the mathematical model of the UAV into two subsystems, a linear attitude control loop and a non-linear position control loop. A backstepping-based outer position controller is then designed that interfaces seamlessly with the inner attitude controller of the cascaded control system. The closed-loop stability is established using a rigorous Lyapunov–Krasovskii analysis under the influence of distributed network time delays. Using the directed graph topology and a distributed backstepping structure, it is shown that the stability criterion is delay-independent. The proposed control algorithms are verified in simulation and then implemented in hardware, and actual flight test experiments prove the validity of these algorithms. |
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ISSN: | 1751-8644 1751-8652 |
DOI: | 10.1049/iet-cta.2019.1151 |