Modelling of Rotational Speed of a Digital Spin Coater Using Multi-Level Periodic Perturbation Signals
Dhidik Prastiyanto, FT Pendidikan Teknik Elektro and Sutikno Madnasri, - and Esa Apriaskar, - and Nur A. Salim, - and Oky P. Pamungkas, - and Arindi Imanindi, - and Wahyu Caesandra, - and Tegoeh Tjahjowidodo, - (2022) Modelling of Rotational Speed of a Digital Spin Coater Using Multi-Level Periodic Perturbation Signals. Journal Europeen des Systemes Automatises, 55 (2). pp. 165-170. ISSN 1269-6935
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Abstract
The purpose of this work is to assess mathematical models of a digital spin coater and find the best one to represent its rotational speed behavior. Simulation models were established using a single input-output identification system approach and involved the use of multi�level periodic perturbation signals (MLPPS). The input data was taken from a Pulse�Width-Modulation (PWM) signal for the actuator in the form of MLPPS, while the observed output was from the rotational speed of the spin coater. The prospective models were represented in state-space and transfer function, both in discrete and continuous time domain. Through this study, it was found that the fitness percentage of the models obtained with the utilized approach ranged from 72% to 92% after being validated with the output of the real system. The results also indicate that for the given operating points, candidate model with discrete transfer function TFD3 has the lowest mean squared error (MSE) in average. The findings of this research may serve as a beneficial knowledge prior to controller design of the digital spin coater. Better model may lead to better controller performance that can support to perform uniformity on the film thickness.
Item Type: | Article |
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Uncontrolled Keywords: | spin coating, identification system, black-box modelling, angular velocity, MLPPS, DC motor |
Subjects: | T Technology > TK Electrical and Electronic Engineering |
Fakultas: | Fakultas Teknik > Pendidikan Teknik Elektro, S1 |
Depositing User: | mahargjo hapsoro adi |
Date Deposited: | 21 Feb 2023 07:26 |
Last Modified: | 21 Feb 2023 07:27 |
URI: | http://lib.unnes.ac.id/id/eprint/56302 |
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