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Two Algorithms for Fast and Accurate Passivity-Preserving Model Order Reduction

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4 Author(s)
Ngai Wong ; Dept. of Electr. & Electron. Eng., Hong Kong Univ. ; Balakrishnan, V. ; Cheng-Kok Koh ; Tung-Sang Ng

This paper presents two recently developed algorithms for efficient model order reduction. Both algorithms enable the fast solution of continuous-time algebraic Riccati equations (CAREs) that constitute the bottleneck in the passivity-preserving balanced stochastic truncation (BST). The first algorithm is a Smith-method-based Newton algorithm, called Newton/Smith CARE, that exploits low-rank matrices commonly found in physical system modeling. The second algorithm is a project-and-balance scheme that utilizes dominant eigenspace projection, followed by a simultaneous solution of a pair of dual CAREs through completely separating the stable and unstable invariant subspaces of a Hamiltonian matrix. The algorithms can be applied individually or together. Numerical examples show the proposed algorithms offer significant computational savings and better accuracy in reduced-order models over those from conventional schemes

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Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on  (Volume:25 ,  Issue: 10 )