Qian, K, Li, Z, Asker, A et al. (2 more authors) (2021) Robust Iterative Learning Control for Pneumatic Muscle with State Constraint and Model Uncertainty. In: 2021 IEEE International Conference on Robotics and Automation (ICRA). 2021 IEEE International Conference on Robotics and Automation (ICRA), 30 May - 05 Jun 2021 IEEE , pp. 5980-5987. ISBN 978-1-7281-9078-5
Abstract
In this paper, we propose a novel iterative learning control (ILC) scheme for precise state tracking of pneumatic muscle (PM) actuators. Two critical issues are considered in our scheme: 1) state constraints on PM position and velocity; 2) uncertainties of the PM model. Based on the three-element form, a PM model is constructed that takes both parametric and nonparametric uncertainties into consideration. By introducing the composite energy function (CEF) approach incorporated with a barrier Lyapunov function (BLF), full state constraints of PM will not be violated and uncertainties are effectively compensated. Through rigorous analysis, we show that under proposed ILC scheme, uniform convergence of PM state tracking errors are guaranteed. Simulation results validate the performance of the proposed scheme.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 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. |
Keywords: | Robust control , Actuators , Uncertainty , Automation , Simulation , Conferences , Muscles |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/S019219/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 May 2022 14:05 |
Last Modified: | 04 May 2022 14:05 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/icra48506.2021.9560892 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186368 |