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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.