Adaptive Neural Altitude Control and Attitude Stabilization of a Hexacopter with Uncertain Dynamics

Ahmad Jobran Al-Mahasneh, S. Anavatti, Meftahul Ferdaus, M. Garratt
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引用次数: 6

Abstract

Unmanned Aerial Vehicles (UAVs) are recently attracting significant research attention due to their potential applications in many fields. Hexacopter UAV offers higher payloads handling and faults tolerance than a quadcopter but its control is a demanding task. In this paper, an adaptive Neural Networks (NN) controller is proposed for altitude tracking and attitude stabilization of a hexacopter UAV with uncertain dynamics. The controller design, simulation and robustness against gust disturbances are discussed. Also, the controller performance is compared with a standard Filtered-Proportional-Derivative-Integrator (FPID) controller for different control scenarios.
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具有不确定动力学的六旋翼机自适应神经高度控制与姿态稳定
近年来,无人驾驶飞行器(uav)因其在许多领域的潜在应用而引起了人们的广泛关注。六旋翼无人机比四旋翼无人机提供更高的有效载荷处理和容错能力,但其控制是一项要求很高的任务。针对具有不确定动力学特性的六旋翼无人机的高度跟踪和姿态稳定问题,提出了一种自适应神经网络控制器。讨论了控制器的设计、仿真和对阵风干扰的鲁棒性。此外,针对不同的控制场景,将该控制器的性能与标准滤波-比例-导数-积分(FPID)控制器进行了比较。
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