An Investigation on the Methodology and Technique of Model Reduction

Abstract In this paper an attempt is made to search for new computational methods of model reduction which will overcome the chief drawbacks of the current methods, such as the possibility of open-loop instability and the large error in the middle-frequency range. The principle of an optimal allotment of the informational resources in n reduced-order model and the technique of separate treatments for middle-frequency and low-frequency ranges are presented. Two methods based upon these concepts are offered. Results of computation show convincingly that these new methods of model reduction are superior to the current methods from the point-of-view of a better similitude to the original model over a wide range of frequency. They are also simple to use and versatile in application.