Identification of Box-Jenkins models for Parameter-Varying Spatially Interconnected systems

This paper presents an identification technique to identify models for Parameter-Varying Spatially Interconnected systems. The main focus of the note is the case when there is additive colored noise in the output of the data generating system. A Refined Instrumental Variable method is proposed to identify parameter-varying spatially interconnected models with Box-Jenkins structure. The technique allows identification of models for general multi-dimensional systems, which may be separable or non-separable, causal, semi-causal (spatially interconnected systems) or non-causal. The effectiveness of the method is shown with application to simulation example.