Articles | Volume 13, issue 1
Mech. Sci., 13, 427–436, 2022
https://doi.org/10.5194/ms-13-427-2022

Special issue: Advances in Service and Industrial Robotics – RAAD2021

Mech. Sci., 13, 427–436, 2022
https://doi.org/10.5194/ms-13-427-2022
Research article
04 May 2022
Research article | 04 May 2022

Payload-adaptive iterative learning control for robotic manipulators

Kaloyan Yovchev and Lyubomira Miteva

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Short summary
Industrial robots are required to perform a given task repetitively with high tracking precision. Iterative learning control (ILC) calculates the tracking error of each iteration and corrects the output control signals in accordance with a predefined learning operator. This research considers the changes of the dynamics characteristics when the robot has different types of payload. It provides an approach for adaptation of the ILC to the specific payload to achieve faster convergence.