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Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm

Biped robots have attracted increasing attention because of their flexible movement and strong adaptability to the surroundings. However, the small output torque and the weak impact resistance of the motor drive, as well as the large energy consumption of the hydraulic drive limit the performance of...

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Autores principales: Zhao, Pengyu, Xie, Anhuan, Zhu, Shiqiang, Kong, Lingyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807574/
https://www.ncbi.nlm.nih.gov/pubmed/36593305
http://dx.doi.org/10.1038/s41598-022-26852-1
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author Zhao, Pengyu
Xie, Anhuan
Zhu, Shiqiang
Kong, Lingyu
author_facet Zhao, Pengyu
Xie, Anhuan
Zhu, Shiqiang
Kong, Lingyu
author_sort Zhao, Pengyu
collection PubMed
description Biped robots have attracted increasing attention because of their flexible movement and strong adaptability to the surroundings. However, the small output torque and the weak impact resistance of the motor drive, as well as the large energy consumption of the hydraulic drive limit the performance of the biped robot drive system. Aiming at these shortcomings, an electric-hydraulic hybrid drive system of biped robot was proposed in this paper. The robot platform was designed based on the prototype of the Zhejiang Lab biped robot. The model of the hydraulic drive system and mechanical structure was established to analyze the dynamic characteristic and the load force during walking. The value function reflecting the energy consumption of the hydraulic drive system was proposed. The pressure of the accumulator in the hydraulic power unit was selected as the control parameter. In order to get the minimum value of the value function, so as to reduce the energy consumption of the hydraulic driving system, the control parameters were optimized by using the genetic algorithm. From the simulation results, the proposed optimization algorithm can improve efficiency by 3.49%.
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spelling pubmed-98075742023-01-04 Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm Zhao, Pengyu Xie, Anhuan Zhu, Shiqiang Kong, Lingyu Sci Rep Article Biped robots have attracted increasing attention because of their flexible movement and strong adaptability to the surroundings. However, the small output torque and the weak impact resistance of the motor drive, as well as the large energy consumption of the hydraulic drive limit the performance of the biped robot drive system. Aiming at these shortcomings, an electric-hydraulic hybrid drive system of biped robot was proposed in this paper. The robot platform was designed based on the prototype of the Zhejiang Lab biped robot. The model of the hydraulic drive system and mechanical structure was established to analyze the dynamic characteristic and the load force during walking. The value function reflecting the energy consumption of the hydraulic drive system was proposed. The pressure of the accumulator in the hydraulic power unit was selected as the control parameter. In order to get the minimum value of the value function, so as to reduce the energy consumption of the hydraulic driving system, the control parameters were optimized by using the genetic algorithm. From the simulation results, the proposed optimization algorithm can improve efficiency by 3.49%. Nature Publishing Group UK 2023-01-02 /pmc/articles/PMC9807574/ /pubmed/36593305 http://dx.doi.org/10.1038/s41598-022-26852-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhao, Pengyu
Xie, Anhuan
Zhu, Shiqiang
Kong, Lingyu
Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
title Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
title_full Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
title_fullStr Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
title_full_unstemmed Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
title_short Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
title_sort pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807574/
https://www.ncbi.nlm.nih.gov/pubmed/36593305
http://dx.doi.org/10.1038/s41598-022-26852-1
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