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Backstepping Sliding Mode Control Based on Extended State Observer for Hydraulic Servo System

by Zhenshuai Wan*, Yu Fu, Chong Liu, Longwang Yue

School of Mechanical and Electrical Engineering, Henan University of Technology, Zhengzhou, China

* Corresponding Author: Zhenshuai Wan. Email: email

Intelligent Automation & Soft Computing 2023, 36(3), 3565-3581. https://doi.org/10.32604/iasc.2023.036601

Abstract

Hydraulic servo system plays an important role in industrial fields due to the advantages of high response, small size-to-power ratio and large driving force. However, inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking performance. To deal with these difficulties, this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interference ability. For this purpose, the nonlinear dynamic model is firstly established, where the nonlinear behaviors and modeling uncertainties are lumped as one term. Then, the extended state observer is introduced to estimate the lumped disturbance. The system stability is proved by using the Lyapunov stability theorem. Finally, comparative simulation and experimental are conducted on a hydraulic servo system platform to verify the efficiency of the proposed control scheme.

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APA Style
Wan, Z., Fu, Y., Liu, C., Yue, L. (2023). Backstepping sliding mode control based on extended state observer for hydraulic servo system. Intelligent Automation & Soft Computing, 36(3), 3565-3581. https://doi.org/10.32604/iasc.2023.036601
Vancouver Style
Wan Z, Fu Y, Liu C, Yue L. Backstepping sliding mode control based on extended state observer for hydraulic servo system. Intell Automat Soft Comput . 2023;36(3):3565-3581 https://doi.org/10.32604/iasc.2023.036601
IEEE Style
Z. Wan, Y. Fu, C. Liu, and L. Yue, “Backstepping Sliding Mode Control Based on Extended State Observer for Hydraulic Servo System,” Intell. Automat. Soft Comput. , vol. 36, no. 3, pp. 3565-3581, 2023. https://doi.org/10.32604/iasc.2023.036601



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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