journal article·2024-11-29Open access

Oscillation Suppression Method of Digital Proportional Valve Based on Fuzzy Intelligent PID Control

Nana Li, Chenglong Dong, Liejiang Wei, Hong Ji, Xiaokang He, Xinqiang Liu

Applied Sciences· Volume 14· Issue 23

Abstract

A digital proportional valve is constituted by the main spool and a high-speed on/off valve bridge acting as the pilot stage. However, the main spool will generate oscillation during movement under the control of the pilot stage. This results in poor stability, slow response speed, low control accuracy, and even the potential loss of control of the valve. To tackle this issue, an oscillation suppression method based on fuzzy intelligent proportional-integral-derivative (PID) control is put forward. The movement state of the main spool is determined in accordance with its movement position and velocity. Thereafter, the fuzzy control parameters of the controller are calculated on the basis of the determined movement state of the main spool. Different PID parameters are adopted to eliminate the control effect difference caused by the structural asymmetry of the two pilot control chambers of the main valve. The performance and robustness of the proposed control method are verified by comparison with the PID controller based on full-bridge and half-bridge control. The results demonstrate that the proposed control method can effectively suppress the oscillation of the main spool of the digital proportional valve, improve the control accuracy, and reduce the response time. When the excitation signal takes the form of a step signal, the overshoot of the control method put forward in this paper is diminished by 26.2% in comparison with that of the PID control. Under stable operating conditions, the maximum tracking error is less than 3.1%. Moreover, compared with simply using the PID control method, this error is reduced by 41%.
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Research context

OpenAlex topics: Iterative Learning Control Systems · Hydraulic and Pneumatic Systems · Advanced Sensor and Control Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Key Laboratory of Advanced Pumps, Valves and Fluid Control System of the Ministry of Education, Lanzhou University of Technology, Lanzhou 730050, China

Funding

National Natural Science Foundation of China · National Key R & D Program of China

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