论文标题
机器人车辆控制的三维移动路径,具有最低正向速度的机器人车辆
Three Dimensional Moving Path Following Control for Robotic Vehicles with Minimum Positive Forward Speed
论文作者
论文摘要
本文解决了沿着在三个维度移动的参考框架指定的几何路径上转向机器人车辆的问题,称为移动路径以下(MPF)运动控制问题。 MPF运动控制问题是针对需要最低正向速度运行的大型机器人车辆解决的,这构成了其他约束,并使用几何概念开发,其中态度控制问题是在特殊的正交组上提出的(3)。此外,提出的控制定律源自新型的MPF误差模型公式,该制定允许通过启用沿参考路径移动的虚拟点进展的明确控制,从而将车辆初始位置的保守约束在车辆的初始位置上排除。然后,MPF控制法的任务是将车辆转向移动路径并汇聚到虚拟点。使用输入到国家稳定性概念提供了正式的稳定性和收敛保证。特别是,我们表明所提出的控制器可以通过自动驾驶仪和风阵进行不完美的跟踪错误。提出了仿真结果,以说明拟议的MPF控制定律的功效。
This paper addresses the problem of steering a robotic vehicle along a geometric path specified with respect to a reference frame moving in three dimensions, termed the Moving Path Following (MPF) motion control problem. The MPF motion control problem is solved for a large class of robotic vehicles that require a minimum positive forward speed to operate, which poses additional constraints, and is developed using geometric concepts, wherein the attitude control problem is formulated on Special Orthogonal group SO(3). Furthermore, the proposed control law is derived from a novel MPF error model formulation that allows to exclude the conservative constraints on the initial position of the vehicle with respect to the reference path by enabling the explicit control of the progression of a virtual point moving along the reference path. The task of the MPF control law is then to steer the vehicle towards the moving path and converge to the virtual point. Formal stability and convergence guarantees are provided using the Input-to-State Stability concept. In particular, we show that the proposed controller is robust to imperfect tracking errors by the autopilot and wind gusts. Simulation results are presented to illustrate the efficacy of the proposed MPF control law.