Errors-In-Variables Identification in Dynamic Networks by an Instrumental Variable Approach

Abstract In this paper, the objective is to obtain an estimate of a particular module embedded in a dynamic network using noisy measurements of the internal variables. This is an extension of the errors-in-variables (EIV) framework to the case of dynamic networks. The consequence of measuring the variables with noise is that the prediction error identification methods no longer result in consistent estimates. The method proposed in this paper is based on a combination of the instrumental variable approach and closed-loop prediction-error identification methods.