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Hidden and transient chaotic attractors in the attitude system of quadrotor unmanned aerial vehicle

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  • Bi, Haiyun
  • Qi, Guoyuan
  • Hu, Jianbing
  • Faradja, Philippe
  • Chen, Guanrong

Abstract

Currently, research of quadrotor unmanned aerial vehicles (QUAV) focuses on the design of the controller and optimization of the control algorithm. Dynamical analysis of the attitude system of QUAV has also been studied. In this paper, the stability of equilibrium points is further analyzed based on their distribution and bifurcation. Multi-initial phase-portraits demonstrate the multistability and the dynamical process from sinks to chaos of the system. The axis of its yaw angular velocity is proven to be a stable manifold, but a little perturbation to it leads to chaotic motion of the QUAV subject to an appropriate parameter configuration. Multi-initial phase-portraits, multi-initial bifurcation diagrams and basins of attraction altogether confirm that the discovered chaotic attractors are hidden and transient. The transient characteristic of these hidden attractors is investigated, revealing that they are natural sinks, which is confirmed by very long-time simulations.

Suggested Citation

  • Bi, Haiyun & Qi, Guoyuan & Hu, Jianbing & Faradja, Philippe & Chen, Guanrong, 2020. "Hidden and transient chaotic attractors in the attitude system of quadrotor unmanned aerial vehicle," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
  • Handle: RePEc:eee:chsofr:v:138:y:2020:i:c:s0960077920302150
    DOI: 10.1016/j.chaos.2020.109815
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    References listed on IDEAS

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    4. Haiyun Bi & Guoyuan Qi & Jianbing Hu, 2019. "Modeling and Analysis of Chaos and Bifurcations for the Attitude System of a Quadrotor Unmanned Aerial Vehicle," Complexity, Hindawi, vol. 2019, pages 1-16, October.
    5. Qi, Guoyuan & Chen, Guanrong & Du, Shengzhi & Chen, Zengqiang & Yuan, Zhuzhi, 2005. "Analysis of a new chaotic system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(2), pages 295-308.
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    Cited by:

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    2. Shaojie Ai & Jia Song & Guobiao Cai, 2022. "Sequence-to-Sequence Remaining Useful Life Prediction of the Highly Maneuverable Unmanned Aerial Vehicle: A Multilevel Fusion Transformer Network Solution," Mathematics, MDPI, vol. 10(10), pages 1-23, May.

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