Short Title: Int. J. Mech. Eng. Robot. Res.
Frequency: Bimonthly
Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-10-25
2024-09-24
Manuscript received April 1, 2024; revised May 31, 2024; accepted June 13, 2024; published September 23, 2024
Abstract—In control applications involving motion control, precise control of the Industrial Hydraulics Actuator (IHA) is necessary to accurately assess the position of the actuator rod. Non-recursive identification is used to model the system with an open-loop and closed-loop approach for this paper. The grey box approach is used to estimate the continuous model and parameter estimation for the system. The System Identification toolbox in MATLAB is used for the model estimation. The process starts by obtaining the input-output data from the experimental work. The input-output data validation outcome reveals a best-fit percentage for open-loop 88.91% and closed-loop 95.43%, as well as a small Root Mean Square Error (RMSE). This indicates a successful validation between the estimated model and the actual system due to a high degree of agreement. The open-loop and closed-loop identification have proven successful as there is no noteworthy disparity in the outcomes. The closed-loop system can be applied to unstable systems and any potential system.Keywords—industrial hydraulics actuator, system identification, grey box, open-loop, closed-loop, root mean square errorCite: Nur Husnina Mohamad Ali, Rozaimi Ghazali, Hazriq Izzuan Jaafar, Muhammad Fadli Ghani, Chong Chee Soon, and Zulfatman Has, "Comparison Study between Open-Loop and Closed-Loop Identification for Industrial Hydraulics Actuator System," International Journal of Mechanical Engineering and Robotics Research, Vol. 13, No. 5, pp. 516-521, 2024.Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.