Model based on the reinitialised partial moments for initialising output-error identification methods

Abstract

The present study addresses the initialisation problem of output-error (OE) identification methods. The challenge is to find a suitable initialization, which brings about a convergence towards the global optimum. A common way to initialise OE methods is to use the ARX model, but it must be used cautiously. The purpose of this study is to describe an alternative method based on the reinitialised partial moment (the RPM model) and to compare this approach with the ARX model by analysing the bias. The RPM model property is an implicit embedded filter that substitutes the explicit data filter required by the ARX model.