MIXED-REALITY ENVIRONMENT FOR ONLINE SYSTEM IDENTIFICATION OF NONLINEAR SYSTEMS
S., A., A., S., T., T. (2008). MIXED-REALITY ENVIRONMENT FOR ONLINE SYSTEM IDENTIFICATION OF NONLINEAR SYSTEMS. EKB Journal Management System, 13(13th International Conference on Applied Mechanics and Mechanical Engineering.), 32-43. doi: 10.21608/amme.2008.39373
ASHRAF I. S.; SABER A.; TAREK T.. "MIXED-REALITY ENVIRONMENT FOR ONLINE SYSTEM IDENTIFICATION OF NONLINEAR SYSTEMS". EKB Journal Management System, 13, 13th International Conference on Applied Mechanics and Mechanical Engineering., 2008, 32-43. doi: 10.21608/amme.2008.39373
S., A., A., S., T., T. (2008). 'MIXED-REALITY ENVIRONMENT FOR ONLINE SYSTEM IDENTIFICATION OF NONLINEAR SYSTEMS', EKB Journal Management System, 13(13th International Conference on Applied Mechanics and Mechanical Engineering.), pp. 32-43. doi: 10.21608/amme.2008.39373
S., A., A., S., T., T. MIXED-REALITY ENVIRONMENT FOR ONLINE SYSTEM IDENTIFICATION OF NONLINEAR SYSTEMS. EKB Journal Management System, 2008; 13(13th International Conference on Applied Mechanics and Mechanical Engineering.): 32-43. doi: 10.21608/amme.2008.39373

MIXED-REALITY ENVIRONMENT FOR ONLINE SYSTEM IDENTIFICATION OF NONLINEAR SYSTEMS

The International Conference on Applied Mechanics and Mechanical Engineering
Article 69, Volume 13, 13th International Conference on Applied Mechanics and Mechanical Engineering., May 2008, Pages 32-43    PDF (446.23 K)
Document Type: Original Article
DOI: 10.21608/amme.2008.39373
Authors
ASHRAF I. S.1; SABER A.2; TAREK T.1
1Assistant professor, Dpt. of Mechatronics, Philadelphia University, Amman, Jordan.
2Associate professor, Dpt. of Mechatronics, Philadelphia University, Amman, Jordan.
Abstract
ABSTRACT
This paper presents a method to identify non-linear-systems in a real time environment.
Acquiring the system's transfer function accurately could be extremely difficult once it
has been assembled, which causes a great difficulty in the non-linear system modeling
and control. Therefore in this research, Mixed Reality Environment (MRE) has been
employed to identify the system's transfer function using Auto-Regressive Moving
Average (ARMAX) model algorithm in order to avoid the complexity associated with
nonlinear systems modeling. Online system identification can be conducted effectively
and efficiently using the proposed method. The advantages of the proposed method are
high accuracy in the identified system, simplicity, and low cost. The results obtained
from on line experimental measured data are used to determine discrete transfer
function of the system, 4th order model with one step prediction shows best
performance.
Keywords
On-line Identification; Auto-Regressive Moving-Average; Pneumatic servo drive; Mixed Reality Environment
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