Dynamic network identification using the direct prediction-error method

The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper this problem is generalized to linear dynamical systems that operate in a complex interconnection structure and the dynamical relationships between the measured variables signals need to be identified. It is shown that the classical Direct Method of closed-loop identification in the prediction-error context can be generalized to provide consistent model estimates, under specified experimental circumstances.