Performance Measure of Some Subspace-Based Methods for Closed-Loop System Identification

This paper presents some of the methods under subspace-based family to perform closed-loop system identification. Three methods have been observed, those are the ORT method, MOESP method and CCA method. The performance of these models is evaluated by identifying the same experimental systems. Three performance evaluation tests according to mean square errors, variance accounted for and best fit are used to verify the accuracy of the models to identify the given systems. The noise model is also introduced in order to see whether the developed model can improve the overall identification performance or not. Based on the simulation results, some justifications are made as to conclude the efficacy of the observed models to identify a closed-loop data system.