A comparison of classical and learning controllers

Joseph Sun De La Cruz, Dana Kulić, William Owen

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

This paper focuses on evaluating Locally Weighted Projection Regression (LWPR) as an alternative control method to traditional model-based control schemes. LWPR is used to estimate the inverse dynamics function of a 6 degree of freedom (DOF) manipulator. The performance of the resulting controller is compared to that of the resolved acceleration and the adaptive computed torque (ACT) controller. Simulations are carried out in order to evaluate the position and orientation tracking performance of each controller while varying trajectory velocities, end effector loading and errors in the known parameters. Both the adaptive controller and LWPR controller have comparable performance in the presence of parametric uncertainty including friction. The ACT controller outperforms LWPR when the dynamic structure is accurately known and the trajectory is persistently exciting.

Original languageEnglish
Title of host publicationProceedings of the 18th IFAC World Congress
PublisherElsevier - International Federation of Automatic Control (IFAC)
Pages1102-1107
Number of pages6
Edition1 PART 1
ISBN (Print)9783902661937
DOIs
Publication statusPublished - 1 Jan 2011
Externally publishedYes

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume44
ISSN (Print)1474-6670

Keywords

  • Adaptive control
  • Learning control
  • Robot dynamics

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