Distributed hunting problem of multi-quadrotor systems via bearing constraint method subject to time delays

Xu, Zhen; Xu, Mingchu; Wu, Yifei; Chen, Qingwei; Zhang, Enze

doi:10.1016/j.jfranklin.2020.05.018

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…6.1, it comes to be evident to relate the corresponding peaks on the signals to the corresponding translation DOFs at which they are coupled, such that a change in the desired orientation occurs as the translational desired behavior changes. In comparison with previous results (see for instance [19,39,44,55,58,61]) and the ones depicted in green in Fig. 6.1, the vehicle operates with no overshoot or oscillation during the transient phase.…”

Section: Simulation Results: the Typical Quadrotor Casesupporting

confidence: 71%

“…In comparison with previous results (see for instance Steed et al (2016), López-Herńandez et al (2019), Xu et al (2020), Castillo-Zamora et al (2021b), Mofid et al (2021), and Sharma and Kar (2021)) and the ones depicted in green in Figure 5, the vehicle operates with no overshoot or oscillation during the transient phase. The latter occurs as the real part of the dominant roots, for the case depicted in green, is lesser than the corresponding σ yet, and these roots have an imaginary component since it is impossible, by the approach in Castillo-Zamora et al (2021b), to know the exact location of the dominant roots; meanwhile, the MID tuning criteria proposed in this work allows one to place the dominant roots exactly over the real axis.…”

Section: Simulation Resultssupporting

confidence: 67%

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Time-delay control of quadrotor unmanned aerial vehicles: a multiplicity-induced-dominancy-based approach

Castillo-Zamora

Boussaada

Benarab

et al. 2022

Journal of Vibration and Control

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The current work exploits the effects of time-delays on the stability of unmanned aerial vehicles s). In this regard, the main contribution is a symbolic/numeric application of the multiplicity-induced-dominancy property in the control of unmanned aerial vehicles rotorcrafts featuring time-delays. The multiplicity-induced-dominancy property is considered to address two of the most representative aerial robotic platforms: a classical quadrotor vehicle and a quadrotor vehicle endowed with tilting rotors. The aforementioned property leads to an effective delayed feedback control design (multiplicity-induced-dominancy tuning criteria), allowing the system to meet prescribed behavior conditions based on the placement of the rightmost root of the corresponding closed-loop characteristic function/quasipolynomial. Lastly, the results of detailed numerical simulations, including the linear and non-linear dynamics of the vehicle, are presented and discussed to validate the proposal.

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Section: Simulation Results: the Typical Quadrotor Casesupporting

confidence: 71%

Section: Simulation Resultssupporting

confidence: 67%

Time-delay control of quadrotor unmanned aerial vehicles: a multiplicity-induced-dominancy-based approach

Castillo-Zamora

Boussaada

Benarab

et al. 2022

Journal of Vibration and Control

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“…Chen et al 32 design a backstepping‐based controller to make all robots rotate around the center obtained by the consensus algorithm. Xu et al 33 construct dynamic hunting models and a hunting protocol based on bearing constraint, which realizes the spiral formation around the target. Most of the above methods design control laws under ideal conditions to achieve encircling control of the target.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement learning method for target hunting control of multi‐robot systems with obstacles

Fan

Yang

Liu

et al. 2022

Int J of Intelligent Sys

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Aiming at the target encirclement problem of multi‐robot systems, a target hunting control method based on reinforcement learning is proposed. First, the Markov game modeling for the multi‐robot system is carried out. According to the task of hunting, potential energy models are designed to meet the requirements of arriving at the desired state and avoiding obstacles. The multi‐robot reinforcement learning algorithm guided by the potential energy models is presented to perform the hunting, where reinforcement learning principles are combined with the model control. Secondly, based on the potential energy models, the target‐tracking hunting strategy and the target‐circumnavigation hunting strategy are established. In the former, the consensus tracking of multi‐robot systems is achieved by designing the velocity potential energy function. And in the latter, virtual circumnavigation points are added to construct the potential energy function, which realizes the desired circumnavigation. Finally, the effectiveness of target hunting control based on the multi‐robot reinforcement learning method is verified by simulation.

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Fully Distributed Multi-UAV Cooperative Hunting with External Disturbance

Xiang

Dong

Wang

et al. 2023

Lecture Notes in Electrical Engineering

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Distributed hunting problem of multi-quadrotor systems via bearing constraint method subject to time delays

Cited by 5 publications

References 10 publications

Time-delay control of quadrotor unmanned aerial vehicles: a multiplicity-induced-dominancy-based approach

Time-delay control of quadrotor unmanned aerial vehicles: a multiplicity-induced-dominancy-based approach

Reinforcement learning method for target hunting control of multi‐robot systems with obstacles

Fully Distributed Multi-UAV Cooperative Hunting with External Disturbance

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