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UAV efficient PID and LQR controllers design based on its stochastic state space dynamics model including disturbances

机译:基于包括干扰的随机状态空间动力学模型的无人机有效PID和LQR控制器设计

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This paper explores the recent efforts to improve the functionality of Unmanned Aerial Vehicles (UAVs) for active interaction and manipulation of objects in addition to making the loss of human lives and economic costs as low as possible. The manipulator movement with an unknown payload was analyzed concerning force and moment disturbances, which influence the mass distribution, and the center of gravity. Hence, a comprehensive dynamics mathematical model of a hexacopter is presented where the stochastic state-space model was derived in order to construct anti-disturbances controllers. Based on the compound pendulum method, the disturbances model was inserted into the stochastic model that simulates the robotic arm with a payload. This research presents a simulation study using LabVIEW, where two types of controllers, the proportional integral differential (PID) and the linear quadratic regulator (LQR) are presented in order to investigate the stability of a hexacopter relative to the earth frame. The latter constitutes a challenge for UAV control performance especially with the presence of uncertainties and disturbances.
机译:本文探索了最近的努力,除了尽可能减少人员伤亡和经济损失外,还改善了无人机的主动交互和操纵功能。分析了具有未知有效载荷的机械手的运动,涉及力和力矩扰动,这些扰动会影响质量分布和重心。因此,提出了一种六旋翼飞机的综合动力学数学模型,其中导出了随机状态空间模型以构造抗干扰控制器。基于复合摆法,将干扰模型插入到随机模型中,该模型模拟了带有有效载荷的机械臂。这项研究提出了使用LabVIEW进行的仿真研究,其中提出了两种类型的控制器,比例积分微分(PID)和线性二次调节器(LQR),以研究六轴直升机相对于土架的稳定性。后者对无人机控制性能构成挑战,特别是在存在不确定性和干扰的情况下。

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