Mohamad Ali, Nur Husnina and Ghazali, Rozaimi and Rahzani, Nayli and Jaafar, Hazriq Izzuan and Ghani, Muhamad Fadli and Chong, Chee Soon (2024) Analyzing model order estimation in industrial hydraulics system using open loop identification. In: 2024 IEEE 14th International Conference on Control System, Computing and Engineering (ICCSCE), 23 August 2024 through 24 August 2024, Penang, Malaysia.
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Analyzing Model Order Estimation in Industrial Hydraulics System using Open Loop Identification.pdf Restricted to Registered users only Download (3MB) |
Abstract
This paper employs system identification to characterize Industrial Hydraulics System (IHS) system using an open-loop method. It utilizes a black box approach for estimating the model and parameters of the system using MATLAB System Identification Toolbox. The paper presents three data sets and validates the estimated model using statistical methods such as percentage best fit, Root Mean Square Error (RMSE), histogram analysis, and correlation analysis. The process began by obtaining the input-output data from the experimental work. The validation results obtained from the input-output data reveals an average best fit percentage for the three data sets is approximately 85%. The data sets show small RMSE values, histogram analysis reveals a Gaussian distribution and strong evidence of the validity of the IHS model in the correlation analysis. Various orders of analysis were conducted, with the results indicating that a third-order linear system offers the closest representation of the IHS. The IHS has been modeled and validated using black box system identification has proven successful as there is no significant disparity in the outcomes.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Industrial hydraulics system, Black box identification, Root mean square error, Open-loop, Histogram analysis, Correlation analysis, Best fit |
| Divisions: | Faculty Of Electrical Technology And Engineering |
| Depositing User: | NUR FARISAH JAFRIN |
| Date Deposited: | 23 Jul 2026 00:57 |
| Last Modified: | 23 Jul 2026 00:57 |
| URI: | http://eprints.utem.edu.my/id/eprint/29893 |
| Statistic Details: | View Download Statistic |
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