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具有振动幅度约束的不确定两连杆刚柔混合机械臂的运动规划和自适应神经跟踪控制。

Motion Planning and Adaptive Neural Tracking Control of an Uncertain Two-Link Rigid-Flexible Manipulator With Vibration Amplitude Constraint.

出版信息

IEEE Trans Neural Netw Learn Syst. 2022 Aug;33(8):3814-3828. doi: 10.1109/TNNLS.2021.3054611. Epub 2022 Aug 3.

Abstract

This article deals with an uncertain two-link rigid-flexible manipulator with vibration amplitude constraint, intending to achieve its position control via motion planning and adaptive tracking approach. In motion planning, the motion trajectories for the two links of the manipulator are planned based on virtual damping and online trajectories correction techniques. The planned trajectories can not only guarantee that the two links can reach their desired angles, but also have the ability to suppress vibration, which can be adjusted to meet the vibration amplitude constraint by limiting the parameters of the planned trajectories. Then, the adaptive tracking controller is designed using the radial basis function neural network and the sliding mode control technique. The developed controller makes the two links of the manipulator track the planned trajectories under the uncertainties including unmodeled dynamics, parameter perturbations, and persistent external disturbances acting on the joint motors. The simulation results verify the effectiveness of the proposed control strategy and also demonstrate the superior performance of the motion planning and the tracking controller.

摘要

本文针对具有振动幅度约束的不确定两连杆刚柔混合机械手,旨在通过运动规划和自适应跟踪方法实现其位置控制。在运动规划中,基于虚拟阻尼和在线轨迹修正技术,为机械手的两个连杆规划运动轨迹。所规划的轨迹不仅可以保证两个连杆能够达到其期望的角度,而且还具有抑制振动的能力,通过限制规划轨迹的参数,可以将其调整以满足振动幅度约束。然后,使用径向基函数神经网络和滑模控制技术设计自适应跟踪控制器。所开发的控制器使机械手的两个连杆在包括未建模动力学、参数摄动和作用于关节电机的持续外部干扰在内的不确定性下跟踪规划轨迹。仿真结果验证了所提出控制策略的有效性,同时也证明了运动规划和跟踪控制器的优越性能。

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