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Event-Based Time Varying Formation Control for Multiple Quadrotor UAVs with Markovian Switching Topologies

Author

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  • Zhen Zhou
  • Hongbin Wang
  • Zhongquan Hu

Abstract

Time varying formation control problem for a group of quadrotor unmanned aerial vehicles (UAVs) under Markovian switching topologies is investigated through a modified dynamic event-triggered control protocol. The formation shape is specified by a time varying vector, which prescribes the relative positions and bearings among the whole agents. Instead of the general stochastic topology, the graph is governed by a set of Markov chains to the edges, which can recover the traditional Markovian switching topologies in line with the practical communication network. The stability proof for the state space origin of the overall closed-loop system is derived from the singular perturbation method and Lyapunov stability theory. An event-triggered formation control protocol in terms of a dynamically varying threshold parameter is delicately carried out, while acquiring satisfactory resource efficiency, and Zeno behavior of triggering time sequences is excluded. Finally, simulations on six quadrotor UAVs are given to verify the effectiveness of the theoretical results.

Suggested Citation

  • Zhen Zhou & Hongbin Wang & Zhongquan Hu, 2018. "Event-Based Time Varying Formation Control for Multiple Quadrotor UAVs with Markovian Switching Topologies," Complexity, Hindawi, vol. 2018, pages 1-15, April.
    • Handle: RePEc:hin:complx:8124861
    DOI: 10.1155/2018/8124861
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    References listed on IDEAS

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    1. Zhou, Jiamu & Dong, Hailing & Feng, Jianwen, 2017. "Event-triggered communication for synchronization of Markovian jump delayed complex networks with partially unknown transition rates," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 617-629.
    2. Xiwang Dong & Liang Han & Qingdong Li & Zhang Ren, 2016. "Time-varying formation control for double-integrator multi-agent systems with jointly connected topologies," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(16), pages 3829-3838, December.
    3. Yilun Shang & Yamei Ye, 2017. "Leader-Follower Fixed-Time Group Consensus Control of Multiagent Systems under Directed Topology," Complexity, Hindawi, vol. 2017, pages 1-9, March.
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    Cited by:

    1. Jesús Enrique Sierra & Matilde Santos, 2019. "Wind and Payload Disturbance Rejection Control Based on Adaptive Neural Estimators: Application on Quadrotors," Complexity, Hindawi, vol. 2019, pages 1-20, January.

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