High-Precision Control of Industrial Robot Manipulator Based on Extended Flexible Joint Model

Abstract

High-precision industrial manipulators are essential components in advanced manufacturing. Model-based feedforward is the key to realizing the high-precision control of industrial robot manipulators. However, traditional feedforward control approaches are based on rigid models or flexible joint models which neglect the elasticities out of the rotational directions and degrade the setpoint precision significantly. To eliminate the effects of elasticities in all directions, a high-precision setpoint feedforward control method is proposed based on the output redefinition of the extended flexible joint model (EFJM). First, the flexible industrial robots are modeled by the EFJM to describe the elasticities in joint rotational directions and out of the rotational directions. Second, the nonminimum-phase EFJM is transformed into a minimum-phase system by using output redefinition. Third, the setpoint control task is transformed from Cartesian space into joint space by trajectory planning based on the EFJM. Third, a universal recursive algorithm is designed to compute the feedforward torque based on the EFJM. Moreover, the computational performance is improved. By compensating the pose errors caused by elasticities in all directions, the proposed method can effectively improve the setpoint control precision. The effectiveness of the proposed method is illustrated by simulation and experimental studies. The experimental results show that the proposed method reduces position errors by more than 65% and the orientation errors by more than 62%.