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Adaptive Finite-Time Control for Formation Tracking of Multiple Nonholonomic Unmanned Aerial Vehicles with Quantized Input Signals

机译:具有量化输入信号的多种非完整无人飞行器编队跟踪的自适应有限时间控制

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摘要

Signal quantization can reduce communication burden in multiple unmanned aerial vehicle (multi-UAV) system, whereas it brings control challenge to formation tracking of multi-UAV system. This study presents an adaptive finite-time control scheme for formation tracking of multi-UAV system with input quantization. The UAV model contains nonholonomic kinematic model and autopilot model with uncertainties. The nonholonomic states of the UAVs are transformed by a transverse function method. For input quantization, hysteretic quantizers are used to reduce the system chattering and new decomposition is introduced to analyze the quantized signals. Besides, a novel transformation of the control signals is designed to eliminate the quantization effect. Based on the backstepping technique and finite-time Lyapunov stability theory, the adaptive finite-time controller is established for formation tracking of the multi-UAV system. Stability analysis proves that the tracking error can converge to an adjustable small neighborhood of the origin within finite time and all the signals in closed-loop system are semiglobally finite-time bounded. Simulation experiment illustrates that the system can track the reference trajectory and maintain the desired formation shape.
机译:信号量化可以减轻多无人机系统中的通信负担,但对多无人机系统的编队跟踪带来了控制挑战。这项研究提出了一种自适应有限时间控制方案,用于输入量化的多无人机系统的编队跟踪。 UAV模型包含具有不确定性的非完整运动学模型和自动驾驶模型。无人飞行器的非完整状态通过横向函数方法转换。对于输入量化,使用滞后量化器来减少系统抖动,并引入新的分解来分析量化信号。此外,设计了一种新颖的控制信号变换以消除量化效果。基于反推技术和有限时间Lyapunov稳定性理论,建立了自适应有限时间控制器,用于多UAV系统的编队跟踪。稳定性分析证明,跟踪误差可以在有限时间内收敛到原点的可调小邻域,并且闭环系统中的所有信号都是半全局有限时限的。仿真实验表明,该系统可以跟踪参考轨迹并保持所需的地层形状。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第7期|3528092.1-3528092.13|共13页
  • 作者

    Hu Jinglin; Sun Xiuxia; He Lei;

  • 作者单位

    Air Force Engn Univ, Xian 710038, Shaanxi, Peoples R China;

    Air Force Engn Univ, Xian 710038, Shaanxi, Peoples R China;

    Air Force Engn Univ, Xian 710038, Shaanxi, Peoples R China;

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