A load-adaptive controller for humanoid robots

Mingliang Zhou, Fei Meng, Zhaoyang Cai, Tongtong Zhang, Daojian Li, Zhangguo Yu*, Xuechao Chen, Xiaopeng Chen

*Corresponding author for this work

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

Abstract

A crucial problem for humanoid robots is to adapt to the uncertain external environment. Since load is one of the most variable parameters in a humanoid robot and affects the high performance in trajectory tracking, strict requirements for load adaptive controllers have been put forward. In this paper, we present a high performance load-adaptive controller based on BP neural network. The adaptive controller adapt robotic nonlinear systems and the coefficients in the controller can be tuned automatically on-line. The effectiveness of the adaptive controller is confirmed by experiments on BHR-5 humanoid robot.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2056-2060
Number of pages5
ISBN (Electronic)9781479987290
DOIs
Publication statusPublished - 2 Oct 2015
Event5th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015 - Shenyang, China
Duration: 9 Jun 201512 Jun 2015

Publication series

Name2015 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015

Conference

Conference5th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015
Country/TerritoryChina
CityShenyang
Period9/06/1512/06/15

Keywords

  • BP Neural Network
  • Humanoid Robot
  • Load Adaptive
  • Trajectory Tracking

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