On the identification of high-order lightly-damped multivariable systems

This paper describes a practical off-line approach to system identification of very high-order, lightly-damped, multivariable systems. In particular, we address the practical and computational aspects of this problem. We also discuss the various choices that the modeler must make interactively. Our eventual objective is to enable “automated” modeling for such systems by minimizing the burden on the modeler. We begin with sampled measurements of the system´s frequency response to obtain an initial model. This model is further refined based on time-domain data as it becomes available. The method is designed to identify very high-order systems by solving several low-order identification problems using the iterative least squares algorithm of Santhanam-Koerner, coupled with the multi-band strategy of Bayard. The individual solutions are combined to yield a transfer-function matrix model of the overall system. A succinct state-space realization of this estimate may be obtained using standard model reduction methods