Novel hybrid adaptive controller for manipulation in complex perturbation environments

Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne

Abstract

© 2015 Smith et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.

• Journal Article Type: Article
• Acceptance Date: May 6, 2015
• Online Publication Date: Jun 1, 2015
• Publication Date: Jun 1, 2015
• Deposit Date: Sep 3, 2019
• Publicly Available Date: Sep 3, 2019
• Journal: PLoS ONE
• Electronic ISSN: 1932-6203
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 6
• Pages: e0129281
• DOI: https://doi.org/10.1371/journal.pone.0129281
• Keywords: General Biochemistry, Genetics and Molecular Biology; General Agricultural and Biological Sciences; General Medicine
• Public URL: https://uwe-repository.worktribe.com/output/2711760
• Contract Date: Sep 3, 2019