Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
---|---|---|
Article Number | 02009 | |
Number of page(s) | 5 | |
Section | Automation and Nontraditional Manufacturing | |
DOI | https://doi.org/10.1051/matecconf/201817302009 | |
Published online | 19 June 2018 |
Robust control method for bionic gait of machine legs based on time delay feedback
Huali College Guangdong University of Technology, 511325 Guangzhou Zengcheng, China
The bionic machine leg is disturbed by the joint during the walking process, which is easy to produce time delay, which causes the robustness of the control of the machine leg is not good. In order to improve the robustness of the bionic gait control of the machine leg, a robust control method for the bionic gait of the machine leg based on time - delay feedback is proposed. The gait correlation parameters of robot leg are collected by sensor array, and the dynamic model of bionic gait is constructed. The fuzzy controller of bionic gait of robot leg is constructed by using time-delay coupling control method. The delayed feedback control error compensation method of machine leg correction is taken to improve the steady control performance of the robotic leg, reduce the steady-state error, improve the robustness of the control machine leg. The simulation results show that this method is robust to the bionic gait control of the machine leg. The output error of the gait parameter can quickly converge to zero, and the accurate estimation of the attitude parameter is stronger.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.