Castano, JA, Zhou, C orcid.org/0000-0002-6677-0855, Li, Z et al. (1 more author) (2016) Robust Model Predictive Control for humanoids standing balancing. In: 2016 International Conference on Advanced Robotics and Mechatronics (ICARM). 2016 (ICARM), 18-20 Aug 2016, Macau, China. IEEE , pp. 147-152. ISBN 978-1-5090-3364-5
Abstract
This paper presents the implementations of Model Predictive Control for the standing balance control of a humanoid to reject external disturbances. The strategies allow the robot to have a compliant behaviour against external forces resulting in a stable and smooth response. The first, ZMP based controller, compensates for the center of mass deviation while the second, attitude controller, regulates the orientation of the body to counterbalance the external disturbances. These two control strategies are combined as an integrated stabilizer, which further increases the effectiveness. Simulation studies on the COMAN humanoid are presented and the data are analysed. The simulations show significant improvements in rejection of external disturbances compared to an existing compliant stabilizer.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 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: | Robots; Robustness; Acceleration; Stability analysis; Trajectory; Hip; Attitude control |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Apr 2019 14:22 |
Last Modified: | 04 Apr 2019 14:22 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICARM.2016.7606910 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144473 |