Low-rank solutions of Riccati equations for positive real balanced truncations of RLC networks

抄録

This paper presents an efficient iterative method to solve standard and generalized algebraic Riccati equations for RLC networks. The proposed method generates a low-rank solution of the Riccati equation for a positive real balanced truncation. Linear passive RLC networks are index-1 or -2 systems;the proposed method generates a low-rank solution of the standard algebraic Riccati equation for an index-1 system and that of a generalized Riccati equation for an index-2 system. To generate accurate reduced-order models at low and high frequencies, the parameters of the iterative method for solving the Riccati equations are investigated. In general, the balanced truncation accuracy at low frequencies is not necessarily satisfactory, compared to that of (Krylov) projection-based model-order reduction. The accuracy of a reduced-order model at low frequencies can be improved by considering a constant shift parameter.