Analysis of the identification of closed-loop systems using least-squares methods

Publisher Website
Google Scholar
Abstract
This paper presents theory and results concerning the analysis of the identification of closed-loop systems using least-squares methods. The least-squares technique is applied in its normal form and in a modified version developed to cope with the bias problem. The analysis has been established following a mathematical investigation of the problem, and by simulation of different identification experiments applied to different structures of closed-loop systems. The results derived from this analysis show the conditions under which the identifiability of the open-loop process can be ensured, considering different situations such as whether or not there is noise present at the system output and whether or not external signals are used to perform the identification experiments. Practical experiments of closed-loop identification on a micromachine system in use in the Department of Electrical Engineering of the University of Manchester are also described. Results for different experimental conditions are presented through graphs showing both the plant and the identified model outputs for the same sequence of sampled input signals.

This publication has 6 references indexed in Scilit: