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

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.

Automated summary

This article discusses an uncertain two-link rigid-flexible manipulator with vibration amplitude constraint, and aims to achieve its position control through motion planning and adaptive tracking approach. The motion trajectories planning for the manipulator's two links can guarantee reaching desired angles and suppress vibration, while the adaptive tracking controller enables the two links to track the planned trajectories under various uncertainties. Simulation results confirm the effectiveness of the proposed control strategy and the superior performance of motion planning and tracking controller.