Model Reduction of Second-Order Systems

This chapter focuses on the model reduction of standard second-order systems. We discuss both second-order-to-first-order and second-order-to-second-order reduction methods. For second-order-to-first-order reduction we emphasize on balanced truncation and interpolatory projection method. While in the second-order-to-second-order reduction beside the balanced truncation we also consider a method which is performed by projecting the system onto the dominant eigenspace of the Gramians. In all cases the methods are summarized by algorithms. The efficiency of the algorithms are shown by numerical experiments.