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Learning feedforward control for industrial manipulators

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conference contribution
posted on 07.10.2021, 08:07 by Chengyuan LiuChengyuan Liu, Atanas Popov, Alison Turner, Emma Shires, Svetan Ratchev
In this work, an iterative learning control (ILC) algorithm is proposed for industrial manipulators. The proposed ILC algorithm works coordinately with the inverse dynamics of the manipulator and a feedback controller. The entire control scheme has the ability of compensating both repetitive and non-repetitive disturbances; guaranteeing the control accuracy of the first implementation; and improving the control accuracy of the manipulator progressively with successive iterations. In order to build the the convergence of the proposed ILC algorithm, a composite energy function is developed. A case study on a four degree of freedom industrial manipulator is demonstrated to illustrate the effectiveness of the proposed control scheme. By implementing the ILC algorithm, the maximum root mean square error of the control accuracy is improved from 0.0262 rad to 0.0016 rad within ten iterations.

Funding

Innovate UK under Grant 113162

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)

Pages

523 - 528

Source

2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)

Publisher

IEEE

Version

AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publication date

2021-06-25

Copyright date

2021

ISBN

9781665424233

eISSN

2767-9861

Language

en

Depositor

Dr Chengyuan Liu. Deposit date: 6 October 2021