动态过渡下空中机械臂的切换自适应控制框架
A Switched Adaptive Control Framework for Aerial Manipulators Under Dynamic Transitions
- The University of Manchester（曼彻斯特大学）
- International Institute of Information Technology Hyderabad（海得拉巴国际信息技术学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对空中机械臂在动态过渡中的控制难题，提出一种不依赖先验耦合与不确定性知识的切换自适应控制框架，通过切换信号保证稳定，并经实验验证优于现有方法。
AI中文摘要：
空中机械臂代表了空中机器人技术的前沿。尽管潜在地能够执行复杂的交互任务，但在任务执行过程中发生的动态过渡期间控制空中机械臂仍面临重大挑战。由这些过渡产生的系统动力学的突变或非连续变化表明应采用切换方法，然而现有的空中操作方法并非为应对切换机制而设计。此外，大多数现有方法在应对飞行器与机械臂之间的紧密耦合，以及因难以建模此类耦合而产生的状态相关不确定性方面存在不足。我们提出了一种基于切换的自适应控制框架，用于空中机械臂，该框架不依赖于飞行器-机械臂耦合和状态相关不确定性的先验知识。为保证在系统动力学变化下仍能稳定操作，该框架提供了一类切换信号，用以刻画那些系统保证保持稳定的过渡阶段。对比实验进一步验证了所提出的基于切换的框架相对于现有技术的有效性。
英文摘要：
Aerial manipulators represent the forefront of aerial robotics. Although potentially capable of complex interaction tasks, controlling aerial manipulators throughout the dynamic transitions occurring during task execution presents significant challenges. Abrupt or discontinuous changes in system dynamics generated by the transitions suggest the use of a switched approach, yet the available aerial manipulation methods are not designed for coping with switched regimes. In addition, most available methods fall short in coping with the tight couplings between the aerial vehicle and the manipulator, as well as in coping with the state-dependent uncertainties arising from the difficulty in modeling such couplings. We propose a switched-based adaptive control framework for aerial manipulators not relying on a priori knowledge of the vehicle-manipulator couplings and of state-dependent uncertainties. To guarantee stable manipulation despite changes in system dynamics, the framework provides a class of switching signals characterizing those transition phases for which the system is guaranteed to remain stable. Comparative experiments further validate the effectiveness of the proposed switched-based framework over the state of the art.
