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Approximate implicit subspace iteration with alternating directions for LTI system model reduction. (English) Zbl 1212.65258

Summary: We propose an approximate implicit subspace iteration with alternating directions framework for linear time-invariant (LTI) system model reduction. Within this framework, dominant eigensubspaces of the product of the system Gramians are approximated directly. This has advantage over approaches that consider the system Gramians separately. We construct two methods within the framework, one uses the QR updates and the other uses the singular value decomposition updates. Numerical results show the efficiency of the proposed methods.

MSC:

65K10 Numerical optimization and variational techniques
65F30 Other matrix algorithms (MSC2010)
15A24 Matrix equations and identities
93B40 Computational methods in systems theory (MSC2010)
65F10 Iterative numerical methods for linear systems
93B11 System structure simplification

Software:

ARPACK; IRAM; eigs; JDQZ
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Full Text: DOI

References:

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