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A model-based sliding mode control with intelligent distribution for a proportional valve driven by digital valve arrays.

Authors :
Gao, Qiang
Liu, Huayi
Lan, Bo
Zhu, Yong
Source :
ISA Transactions; Aug2024, Vol. 151, p312-323, 12p
Publication Year :
2024

Abstract

Parallel-connected digital valve arrays are commonly utilized in the pilot stage of the proportional directional valve to enhance dynamic performance and reliability. However, when the digital valve array is driven by a digital signal, it is difficult to optimally assign the signal pulses to each valve. If the assignment is not well executed, it can significantly reduce the switching uniformity of the digital valves or lead to performance degradation of the system. In this paper, a model-based sliding mode control strategy based on the intelligent distribution of control law is proposed and successfully applied to a proportional valve driven by digital valve arrays. The intelligent distribution strategy encompasses a logic distribution algorithm and a circular sliding distribution algorithm that automatically assigns control laws to different valves based on the rolling of the PWM signal cycle. Experimental results confirm that the proposed strategy not only simultaneously reduces the total number of valve switches and enhances the switching uniformity among the valves, but also adapts to the variation in the number of valves. The proposed strategy is not limited to the application of digital valve arrays, it is also applicable in other fields of multi-actuators driven by digital signals, and can simultaneously improve the control accuracy, lifetime, and maintenance friendliness. • A digital proportional valve is proposed, where the pilot stage consists of fixed orifices and digital valve arrays. • The intelligent distribution strategy is designed based on a logic distribution and a circular sliding distribution. • The proposed MSMC with intelligent distribution can be adapted to DVAs with any number of valves. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00190578
Volume :
151
Database :
Supplemental Index
Journal :
ISA Transactions
Publication Type :
Academic Journal
Accession number :
178600225
Full Text :
https://doi.org/10.1016/j.isatra.2024.05.027