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Neural Direct Adaptive Active Disturbance Rejection Controller for Electro-hydraulic Servo System

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  • Intelligent Control and Applications
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Abstract

This paper develops a neural direct adaptive active disturbance rejection controller for the electro-hydraulic servo system (EHSS). EHSS in the construction mining machinery is a high-order nonlinear system with uncertainties and heavy external disturbance, which challenges the controller. The proposed control scheme, integrating neural direct adaptive controller and linear extended state observer (LESO), is designed based EHSS’s reduced-order model. The stronger robustness and the improved tracking performance can be expected by using LESO to compensate for remaining uncertainties. In addition, the rationality of reduced-order model and the stability of the proposed controller are proved. Comparative simulation results show that the controller has an excellent position tracking performance.

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Authors and Affiliations

  1. School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China

    De-Yi Zhang, Song-Yong Liu, Yi Chen & Cong-Cong Gu

  2. School of Mechanical Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009, China

    De-Yi Zhang

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  1. De-Yi Zhang
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Correspondence to Song-Yong Liu.

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This work is supported by the National Natural Science Foundation of China (No.51975570), the Xuzhou science and technology achievements transformation plan (KC20203), the Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (TAPP) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

De-Yi Zhang received his Master’s degree in mechanical engineering from Hohai University in 2015. His current research interests include electro-hydraulic servo control, neural network control, and adaptive control.

Song-Yong Liu received his Ph.D. degree in mechanical design and theory from China University of Mining and Technology, in 2009. His research interests include design and dynamics of excavation machinery, and automation engineering.

Yi Chen received his B.S. degree in mechanical design, manufacturing and automation from Huangshan University, in 2018. His research interests include nonlinear control, sliding mode control, and industrial manipulator control.

Cong-Cong Gu received his B.S. degree in mechanical design, manufacturing and automation from Nanjing University of Science and Technology ZiJin College, in 2019. His research interests include nonlinear control and industrial manipulator control.

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Zhang, DY., Liu, SY., Chen, Y. et al. Neural Direct Adaptive Active Disturbance Rejection Controller for Electro-hydraulic Servo System. Int. J. Control Autom. Syst. 20, 2402–2412 (2022). https://doi.org/10.1007/s12555-020-0954-z

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