Accuracy enhancing methods for the frequency-weighted balancing related model reduction

Authors:
  • BAB.D.O. Anderson
    B.D.O. Anderson
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Abstract
In this paper we develop computational techniques with enhanced accuracy for two frequency-weighted model reduction approaches, namely, balanced truncation, and singular perturbation approximation. New stability-enforcing choices of the frequency-weighted grammians can guarantee the stability of reduced models for two-sided frequency weights. Several numerical examples show the effectiveness of the new approximation techniques.