Lee Y.-HHsu S.-CChi T.-YDu Y.-YHu J.-STsao T.-C.YU-HSIU LEE2022-03-222022-03-22202109574158https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099960031&doi=10.1016%2fj.mechatronics.2021.102487&partnerID=40&md5=2711436f552483314a629b1e635d54c4https://scholars.lib.ntu.edu.tw/handle/123456789/599042Common error sources of industrial robot manipulators include joint servoing error, imprecise kinematics, mechanical compliance, and transmission error. In this work we present a nested loop iterative learning control (ILC) feedforward structure: an inner loop that compensates for motor dynamics, and an outer loop that corrects the deviation along the path tracked, that features practically efficient implementation. Taking advantage of industrial robot's speed reduction transmission, single-input-single-output method is demonstrated effective for the nonlinear coupled robot dynamics. Data-based inversion technique that incorporates motion constraint is used for fast inner loop convergence. The outer loop utilizes inverse Jacobian matrix for joint reference modification. For nonlinear static friction that is difficult to be compensated for with only joint command, notch filtering is utilized in the learning process to avoid exciting vibration inherently exists in the robot. The proposed nested loop ILC requires only the nominal kinematic parameters from the robot manufacturer, and can be readily implemented without modifying the existing robot controllers. The effectiveness of the proposed method is experimentally verified on a six degree-of-freedom robot manipulator. ? 2021 Elsevier LtdData-based dynamic inversionIterative learning control (ILC)Robot manipulatorTrajectory trackingDegrees of freedom (mechanics)ErrorsFlexible manipulatorsIndustrial robotsInverse problemsIterative methodsJacobian matricesKinematicsLearning algorithmsModular robotsNotch filtersRobot applicationsStictionTransmissionsTwo term control systemsEfficient implementationFeedforward structuresInversion techniquesIterative learning controlMechanical complianceSingle input single outputSix degree-of-freedomTrajectory generationIndustrial manipulatorsIndustrial robot accurate trajectory generation by nested loop iterative learning controljournal article10.1016/j.mechatronics.2021.1024872-s2.0-85099960031