Error‐Controlled Model Order Reduction of Second Order Systems with Adaptive Choice of Shifts and Order

This contribution summarizes a novel approach to error-controlled model order reduction of second order systems, i. e. a new way to find a reduced order model of specified approximation quality. To this end, starting from a particular state space realization of the model, one performs multiple reduction steps and increments the reduced model until (computationally affordable) rigorous global error bounds fall below the prescribed limit. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)