Identification and analysis of Servo-Pneumatic System using mixed reality environment.
awad, M., Rabbo, S., El-Arabi, M. (2021). Identification and analysis of Servo-Pneumatic System using mixed reality environment.. EKB Journal Management System, 3(3), 46-52. doi: 10.21608/jisse.2021.95202.1042
magdy naeem awad; Saber A. Rabbo; Mohamed E. El-Arabi. "Identification and analysis of Servo-Pneumatic System using mixed reality environment.". EKB Journal Management System, 3, 3, 2021, 46-52. doi: 10.21608/jisse.2021.95202.1042
awad, M., Rabbo, S., El-Arabi, M. (2021). 'Identification and analysis of Servo-Pneumatic System using mixed reality environment.', EKB Journal Management System, 3(3), pp. 46-52. doi: 10.21608/jisse.2021.95202.1042
awad, M., Rabbo, S., El-Arabi, M. Identification and analysis of Servo-Pneumatic System using mixed reality environment.. EKB Journal Management System, 2021; 3(3): 46-52. doi: 10.21608/jisse.2021.95202.1042

Identification and analysis of Servo-Pneumatic System using mixed reality environment.

Journal of International Society for Science and Engineering
Article 4, Volume 3, Issue 3, September 2021, Page 46-52  XML PDF (813.48 K)
Document Type: Original Article
DOI: 10.21608/jisse.2021.95202.1042
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Authors
magdy naeem awad email orcid 1; Saber A. Rabbo2; Mohamed E. El-Arabi3
1Mechatronics Engineering Department, Canadian international college, 5Th Settlement, Cairo 11835, Egypt.
2Department of Mechanical Engineering, Faculty of Engineering at Shoubra, Benha University, Egypt
3Department of Design and Production Engineering, Faculty of Engineering, Cairo University, Giza, Egypt
Abstract
This paper presents a method to control and identify the servo pneumatic system using a mixed reality environment. A mathematical model is presented to study the system dynamics and nonlinear effects of the servo pneumatic system. The auto-regressive moving-average (ARMA) model-based recursive least squares (RLS) algorithm is utilized to identify the transfer function of the servo pneumatic system in a real-time environment. The identification of the servo pneumatic system can be carried out effectively and efficiently using the proposed ARMA model. Furthermore, the high precision to identify the system with minimum error, and reducing the time in adjusting the parameters of the control unit. The discrete transfer function of the servo pneumatic system is identified in real-time from the inputs and outputs data of the system. The identification results showed that the fourth-order system model achieved the minimum square error with one-step prediction. The experimental results showed the accuracy and effectiveness of the proposed method.
Keywords
Online system identification; Auto-regressive moving-average; Mixed-reality environment; Servo pneumatic system
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