Frequency weighted model order reduction techniques

Abstract

This thesis investigates the frequency weighted balanced model order reduction problem for linear time invariant systems. First, two new frequency weighted balanced truncation techniques based on zero cross-terms are proposed. Both methods are applicable for single-sided weighting, and are based on modifications to Sreeram and Sahlan's technique. The first method uses the properties of all-pass function to transform the original frequency weighted model order reduction problem into an equivalent unweighted model reduction problem, while in the second method. the relationship between the final and the intermediate reduced order model used in Sreeram and Sahlan's technique is derived. Numerical examples show that a significant error reduction can be achieved using both methods.