| Issue |
Int. J. Simul. Multidisci. Des. Optim.
Volume 16, 2025
|
|
|---|---|---|
| Article Number | 27 | |
| Number of page(s) | 12 | |
| DOI | https://doi.org/10.1051/smdo/2025028 | |
| Published online | 21 October 2025 | |
Research Article
NRBO optimized fuzzy active disturbance rejection control for electro-hydraulic position servo system
School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang Henan, 471003, PR China
* e-mail: liyaosong707@163.com
Received:
28
April
2025
Accepted:
8
September
2025
To address the comprehensive control challenges arising from the coupled effects of model uncertainties, parameter perturbations, and external disturbances in electro-hydraulic position servo systems, this study proposes an optimized fuzzy active disturbance rejection control strategy based on the Newton-Raphson-Based Optimizer (NRBO). A fuzzy-compensated active disturbance rejection controller (Fuzzy-ADRC) is developed. This controller introduces fuzzy logic to dynamically compensate for nonlinear disturbances in real time and enhances the system's robustness against external disturbances and uncertainties. To overcome the challenges associated with the numerous parameters and tuning difficulties of ADRC, the NRBO optimization algorithm is integrated to leverage its fast convergence and avoidance of local optima, enabling systematic parameter optimization for the Fuzzy-ADRC (NRBO-Fuzzy-ADRC). Simulation results demonstrate that compared to conventional ADRC control, the proposed NRBO-Fuzzy-ADRC reduces the step response time by 74.3% and decreases the average tracking error in sine responses by 70.1%. This algorithm significantly enhances control performance and provides a novel optimization framework for electro-hydraulic position servo system applications.
Key words: Electro-hydraulic position servo system / NRBO / Fuzzy-ADRC / parameter optimization
© Y. Li et al., Published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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