Issue |
MATEC Web Conf.
Volume 277, 2019
2018 International Joint Conference on Metallurgical and Materials Engineering (JCMME 2018)
|
|
---|---|---|
Article Number | 01007 | |
Number of page(s) | 7 | |
Section | Metallurgy & Control and Manufacturing | |
DOI | https://doi.org/10.1051/matecconf/201927701007 | |
Published online | 02 April 2019 |
Adaptive fractional PID control of biped robots with time-delayed feedback
Department of Physical and Mathematical Sciences, Autonomus University of Nuevo Leon (FCFM,UANL), Cd. Universitaria, San Nicolas de los Garza, Nuevo Leon, 66450, Mexico
* Corresponding author: joel.perezpd@uanl.edu.mx
This paper presents the application of Fractional Order Time- Delay adaptive neural networks to the trajectory tracking for chaos synchronization between Fractional Order delayed plant, reference and Fractional Order Time-Delay adaptive neural networks. The proposed new control scheme is applied via simulations to control of a 4-DOF Biped Robot [1]. The main methodologies, on which the approach is based, are Fractional Order PID the Fractional Order Lyapunov-Krasovskii functions methodology. The structure of the biped robot is designed with two degrees of freedom per leg, corresponding to the knee and hip joints. Since torso and ankle are not considered, it is obtained a 4-DOF system, and each leg, we try to force this biped robot to track a reference signal given by undamped Duffing equation. The tracking error is globally asymptotically stabilized by two control laws derived based on a Lyapunov-Krasovski functional.
© The Authors, published by EDP Sciences, 2019
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.