Finite-Time Prescribed Performance Neural Network Force Control of Electro-Hydraulic Proportional Load Simulator with Output Feedback

This paper focus on the high accuracy force control of electro-hydraulic proportional load simulator (EHPLS). Firstly, to weaken the influence of the unknown dead zone of the proportional valve, a mathematic model with a smooth inverse dead zone was constructed. Then, finite-time prescribed performance function, of which the desired steady-state value can be achieved within finite time, is defined to impose constraints on the tracking error, while the neural network feedback is introduced to compensate for the unknown dynamic, which can ensure the tracking accuracy further improved for the entire tracking process in the presence of unknown dead-zone parameters, unknown system parameters and disturbance. Finally, through design modification, the proposed control technologies are realized based on the output feedback signal. Comparative simulations under two desired force trajectories are carried out to verify the effectiveness of the proposed controller.

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Publication Details

Journal
Actuators
Published
2026-03-04
DOI
https://doi.org/10.3390/act15030150
Primary Topic
Hydraulic and Pneumatic Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Finite-Time Prescribed Performance Neural Network Force Control of Electro-Hydraulic Proportional Load Simulator with Output Feedback

Pengxiang Zhang, C. Li, Long Liu, Zhenle Dong et al.
Actuators
Hydraulic and Pneumatic Systems
article

Finite-Time Prescribed Performance Neural Network Force Control of Electro-Hydraulic Proportional Load Simulator with Output Feedback

Pengxiang Zhang, C. Li, Long Liu, Zhenle Dong, Yilong Jia, Jianyong Yao
article en

Abstract

This paper focus on the high accuracy force control of electro-hydraulic proportional load simulator (EHPLS). Firstly, to weaken the influence of the unknown dead zone of the proportional valve, a mathematic model with a smooth inverse dead zone was constructed. Then, finite-time prescribed performance function, of which the desired steady-state value can be achieved within finite time, is defined to impose constraints on the tracking error, while the neural network feedback is introduced to compensate for the unknown dynamic, which can ensure the tracking accuracy further improved for the entire tracking process in the presence of unknown dead-zone parameters, unknown system parameters and disturbance. Finally, through design modification, the proposed control technologies are realized based on the output feedback signal. Comparative simulations under two desired force trajectories are carried out to verify the effectiveness of the proposed controller.

ActuatorsVol. 15(3)
Aviation Industry Corporation of China (China) (CN), Henan University of Science and Technology (CN), Nanjing University of Science and Technology (CN), Luoyang Institute of Science and Technology (CN)
Openalex Percentile: Top 36%
Hydraulic and Pneumatic Systems
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