Robust design of independent joint control of industrial robots with secondary encoders. (February 2022)

• Record Type: Journal Article
• Authors: Mesmer, Patrick; Neubauer, Michael; Lechler, Armin; Verl, Alexander
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 73(2022)
• Publication Date: 2022-02
• Subjects: Industrial robot -- Control -- Machining -- Structured H-infinity synthesis; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2021.102232
• Languages: English
• ISSNs: 0736-5845

Abstract

Abstract: The independent joint control approach with motor-side velocity and position feedback still dominates most industrial robot applications. Although it is known, that the elasticity of the drivetrains has a significant influence on the achievable dynamic path accuracy. As a result, an increasing number of industrial robots are available that use secondary encoders to measure the joint position. This paper addresses the robust design of independent joint control of industrial robots with secondary encoders under explicit consideration of the drivetrain elasticity. For this purpose, the nonlinear robot dynamics are linearized and the configuration dependency of the mass matrix is treated as structured uncertainty. The trade-off between the velocity control bandwidth and the gain margin of the position control loop is solved by means of a nonsmooth optimization-based H ∞ synthesis. The design method is validated for the three base joints of a KUKA KR210-2 industrial robot. Experimental results for linear Cartesian paths and a milling experiment are presented to confirm the approach. Highlights: The potential of secondary encoders for the independent joint control is analyzed. A robust design method for joint-side position feedback is proposed. A system identification strategy for the joint elasticity is presented. Control strategy improves the quality of robot machined products.