Modeling and Simulation of Hydraulic Proportional Control Valves with Different Types of Controllers

Sarah M. Rashid
Department of Mechatronics Engineering, Al-khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq
Maher Yahya Salloom
Department of Mechatronics Engineering, Al-khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq
Nor Haniza Bakhtiar Jemily
Mechanical Section, University Kuala Lumpur Malaysian Spanish Institute, Kulim Hi-Tech Park, Kulim 09000,Malaysia
Ab- Samat H.
School of Mechanical Engineering, Engineering Campus, University Sains Malaysia (USM), 14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang, Malaysia
Vol. 20 No. 2 (2024)
Vol. 20 No. 2 (2024)
Published 2024-06-01
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Modeling and Simulation of Hydraulic Proportional Control Valves with Different Types of Controllers. (2024). Al-Khwarizmi Engineering Journal, 20(2), 56-64. https://doi.org/10.22153/kej.2024.03.001
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Abstract

Numerous applications have been developed, primarily focusing on achieving platform equilibrium. The system may employ electric motors or hydraulic cylinders, conventional valves, or a control mechanism that utilizes pressure sensors. The majority of these sources exhibit inaccuracies, demonstrate a sluggish response time, and may require periodic reorganization. Before implementing actual systems, it is imperative to develop a virtual system through the utilization of simulation techniques. This research aims to develop and evaluate a platform comprising two hydraulic cylinders and two proportional valves. The design of a hypothetical hydraulic system involves an analysis of the system and the derivation of its transfer function. Subsequently, the performance of the system is assessed by identifying the optimal approach for acquiring the parameters kp, ki, and kd, an examination is conducted to optimize the existing genetic algorithm (GA) PID controller and the particle swarm optimization (PSO) algorithm through the utilization of MATLAB simulation. The results indicate that the genetic algorithm (GA) PID algorithm outperforms the particle swarm optimization (PSO) PID controller in enhancing system performance. The chosen error standard for the self-balance platform control system is the Integral Time Absolute Error (ITAE) type. The system exhibits an improved rate of convergence.

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(Received 30 October 2023; Accepted 31 March 2024; Published 1 June 2024)