Residual vibration suppression using off-line learning input shaping method for a flexible joint robot

Abstract

This paper presents a two-impulse input shaping method using off-line learning method to suppress the residual vibration of a flexible joint robot which is considered as perform repetitive tasks. It has been proved that the two-impulse input shaping method has the ability to suppress time-varying or nonlinear residual vibration. However, the parameters of the input shaper are difficult to select. In this paper, a method based on the off-line learning is presented to determine the proper parameters. We found that the torque of the joint can reflect the residual vibration through analysis of relations between the residual vibration and torque of the flexible joint robot. Thus, the torque signal of the joint is used to measure the vibration magnitude and no additional sensors for vibration measurement are required. For the nonmeasurable of the phase of the residual vibration, only the vibration magnitude is used to update the parameters of the input shaper off-line until the minimum vibration is obtained. The initial parameters of the input shaper also are estimated in this paper. Simulations are conducted to suppress residual vibration of a flexible joint robot, thereby demonstrating the effectiveness of the off-learning learning input shaping method.