THERMAL SCIENCE

International Scientific Journal

IN-DEPTH ANALYSIS AND OPTIMIZATION OF ELECTRONIC CLOSED-LOOP CONTROL FOR PROPORTIONAL ENLARGED VALVES BASED ON SIMULATIONX

ABSTRACT
This paper conducts an in-depth study on the electronic closed-loop control characteristics of Valvistor valves (a type of proportionally enlarged valve) by leveraging the SimulationX simulation platform. The displacement-area relation-ship of a 25 mm diameter Valvistor valve was accurately determined through the combination of experimental measurements and theoretical analyses. A highly realistic SIMULATIONX model was constructed based on actual parameters, taking into account oil compression, leakage, viscous friction and other key factors. The proportional-integral-derivative parameters were initially calculated using the genetic algorithm and then refined through a series of fine-tuning operations. The results show that the optimized proportional-integral-derivative control significantly improves the dynamic characteristics of the valve: in the step response of the main valve displacement, the rising response time is reduced by 45 milliseconds, the descending step response time is shortened by 20 milliseconds, and there is almost no overshoot compared with the original valve. Considering the variable pressure differences at the valve port in actual working conditions, the parameters of the feed-forward controller were corrected. Through iterative simulation of different pressure differences and feed-forward gain values within the range of 0.5-2 MPa, a parameter curve of the feed-forward controller was obtained, which ensures the valve's displacement output meets actual operation requirements under different pressure conditions. The research results provide important theoretical support and practical guidance for optimizing the performance of Valvistor valves and improving the control accuracy of hydraulic systems. Meanwhile, the limitations of the research (lack of physical experiment verification and insufficient universality) are pointed out, and future research directions (conducting physical experiments, expanding applications in complex systems, optimizing control algorithms) are clarified.
KEYWORDS
PAPER SUBMITTED: 2024-12-20
PAPER REVISED: 2025-04-28
PAPER ACCEPTED: 2025-05-05
PUBLISHED ONLINE: 2026-04-12
DOI REFERENCE: https://doi.org/10.2298/TSCI2602159L
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2026, VOLUME 30, ISSUE No. 2, PAGES [1159 - 1167]
REFERENCES
[1] Li, G., et al., Throttle Valve Erosion in the Oil and Gas Industry, J. Mater. Sci., 59 (2024), Nov., pp. 20874-20899
[2] Zylka, M., et al., Numerical Simulation of Pneumatic Throttle Check Valve Using Computational Fluid Dynamics (CFD), Sci Rep 13, (2023), 2475
[3] Liu, H., et al., Flow Control Characteristics of the Digital and Mechanical Redundancy Control Electric Modulation Valve, J. Zhejiang Univ. Sci. A, 23, (2022), Aug., pp. 599-609
[4] Zhao, J., et al., Dynamic Engagement Characteristics of Wet Clutch Based on Hydro-Mechanical Continuously Variable Transmission, J. Cent. South Univ., 28 (2021), June, pp. 1377-1389
[5] Vulic, N., et al., Implementing SimulationX in the Modelling of Marine Shafting Steady State Torsional Vibrations, Polish Maritime Research, 28 (2021), 2, pp. 63-71
[6] Kong, W., et al., PID Control Algorithm Based on Multistrategy Enhanced Dung Beetle Optimizer and Back Propagation Neural Network for DC Motor Control, Sci. Rep., 14 (2024), 28276
[7] Roeva, O., Slavov, T., Fed-Batch Cultivation Control Based on Genetic Algorithm PID Controller Tuning, in: Numerical Methods and Applications, Springer, New York, USA, 2011, Vol 6064
[8] Ahmad, W. N. A.W., et al., Non-Classical Optimal Control Problem: A Case Study for Continuous Approximation of Four-Stepwise Function, Advances in Differential Equations and Control Processes, 30 (2023), 4, pp. 309-321
[9] Tindano, T., et al., Optimal Control of a Nonlinear Elliptical Evolution Problem with Missing Data, Advances in Differential Equations and Control Processes, 30 (2023), 2, pp. 135-150
[10] Mzili, T., et al., Hybrid Genetic and Penguin Search Optimization Algorithm (GA-PSEOA) for Efficient Flow Shop Scheduling Solutions, Facta Universitatis, Series: Mechanical Engineering, 22 (2024), 1, pp. 77-100
[11] Fu, Q., et al., Multi-Objective Optimization Research on VR Task Scenario Design Based on Cognitive Load, Facta Universitatis, Series: Mechanical Engineering, 22 (2024), 2, pp. 293-313
[12] He J.-H., et al., Modeling and Numerical Analysis for an MEMS Graphene Resonator, Front. Phys., 13 (2025), 1551969
[13] He, C.-H., A Variational Principle for a Fractal Nano/Microelectromechanical (N/MEMS) System, Int. J. Numer. Method. H., 33 (2023), 1, pp. 351-359
[14] He, J.-H., Periodic Solution of a Micro-Electromechanical System, Facta Universitatis, Series: Mechanical Engineering, 22 (2024), 2, pp. 187-198
[15] Nadeem, M., et al., Analysis of Nanobeam-Based Microstructure in N/MEMS System Using van der Waals Forces, Facta Universitatis, Series: Mechanical Engineering, 22 (2024), 4, pp. 673-688
[16] Tseng, K. H., et al., Parameter Optimization of Nanosilver Colloid Prepared by Electrical Spark Discharge Method Using Ziegler-Nichols Method, Journal of Physics and Chemistry of Solids, 148 (2021), 109650

© 2026 Society of Thermal Engineers of Serbia. Published by the VinĨa Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence