Hierarchical identification of linear large-scale process plants

摘要

This paper proposes a hierarchical identification technique for linear large-scale processes. It has the aim of reducing the optimization complexity and time necessary to obtain good linear models. The systems to be identified are assumed to be multivariable of unknown dimension, system matrices and statistical information about noise. The technique is suitable for strong parallel processing.