The range error test in the structural identification of linear multivariable systems

Abstract

Among the approaches that have been proposed in recent years for the identification of discrete-time linear multivariable systems, very efficient procedures are based on the introduction of a set of input-output canonical models and on the separate determination of the process structure (structural identification) and parameters (parametric identification). This paper introduces a new simple test which allows us to perform the structural identification without the drawbacks usually associated with singularity tests. The proposed test gives an a priori prediction of the model performance in order to avoid trial and error procedures in the determination of a suitable structure for the process to be identified.