Mixed-Reality Environment for Online System Identification of Nonlinear Systems

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.