Robust Model Predictive Control for Humanoids Standing Balancing

Juan A Castano, Chengxu Zhou, Zhibin Li, Nikos G. Tsagarakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Advanced Robotics and Mechatronics (ARM)
Place of PublicationMacau, China
PublisherInstitute of Electrical and Electronics Engineers
Pages147-152
Number of pages7
ISBN (Electronic)978-1-5090-3364-5
ISBN (Print)978-1-5090-3365-2
DOIs
Publication statusPublished - 27 Oct 2016
Event2016 International Conference on Advanced Robotics and Mechatronics - Macau, China
Duration: 18 Aug 201620 Aug 2016
http://www.ieee-arm.org/

Conference

Conference2016 International Conference on Advanced Robotics and Mechatronics
Abbreviated titleICARM 2016
Country/TerritoryChina
CityMacau
Period18/08/1620/08/16
Internet address

Fingerprint

Dive into the research topics of 'Robust Model Predictive Control for Humanoids Standing Balancing'. Together they form a unique fingerprint.

Cite this