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Fuzzy Feedback Control for Electro-Hydraulic Actuators

Tan Nguyen Van1, Huy Q. Tran2,*, Vinh Xuan Ha3, Cheolkeun Ha4, Phu Huynh Minh1

1 School of Engineering-Technology, Thu Dau Mot University, Thu Dau Mot City, 590000, Vietnam
2 Faculty of Engineering-Technology, Nguyen Tat Thanh University, Ho Chi Minh City, 754000, Vietnam
3 Hue Industrial College, Hue City, 530000, Vietnam
4 Robotics and Mechatronics Lab, University of Ulsan, Ulsan City, 44610, Korea

* Corresponding Author: Huy Q. Tran. Email:

Intelligent Automation & Soft Computing 2023, 36(2), 2441-2456.


Electro-hydraulic actuators (EHA) have recently played a significant role in modern industrial applications, especially in systems requiring extremely high precision. This can be explained by EHA’s ability to precisely control the position and force through advanced sensors and innovative control algorithms. One of the promising approaches to improve control accuracy for EHA systems is applying classical to modern control algorithms, in which the proportional–integral–derivative (PID) algorithm, fuzzy logic controller, and a hybrid of these methods are popular options. In this paper, we developed a novel version of the fuzzy control algorithm and linear feedback control method, namely fuzzy linear feedback control, to improve the control performance. To achieve the highest performance, we first designed a mathematical EHA model based on the Matlab/Simulink software packages thanks to the selected parameters, which are similar to a real EHA system. Then, we respectively applied PID, fuzzy PID (FPID), and fuzzy linear feedback control (FLFC) before comparing them to have a full view of the outstanding advantages of the proposed algorithm. The simulation results showed that the proposed FLFC algorithm is approximately 99% and 77% superior in performance to the PID and feedback control algorithms, respectively.


Cite This Article

T. N. Van, H. Q. Tran, V. X. Ha, C. Ha and P. H. Minh, "Fuzzy feedback control for electro-hydraulic actuators," Intelligent Automation & Soft Computing, vol. 36, no.2, pp. 2441–2456, 2023.

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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