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- W2009017787 abstract "Homotopy approaches have previously been developed for synthesizing H/sub 2/ optimal reduced-order models. Some of the previous homotopy were based on directly solving the optimal projection equations, a set of two Lyapunov equations mutually coupled by a nonlinear term involving a projection matrix /spl tau/, that characterize the optimal reduced-order model. These algorithms are numerically robust but suffer from the curse of large dimensionality. Subsequently, gradient-based homotopy algorithms were developed. To make these algorithms efficient and to eliminate singularities along the homotopy path, the basis of the reduced-order model was constrained to minimal parameterization. However the resultant homotopy algorithms sometimes experienced numerical ill-conditioning or failure due to the minimal parameterization constraint. This paper presents a new homotopy approach the algorithm avoids the large dimensionality of the previous approaches by efficiently solving a pair of Lyapunov equations coupled by low rank linear operators. >" @default.
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- W2009017787 date "2002-12-17" @default.
- W2009017787 modified "2023-09-26" @default.
- W2009017787 title "An efficient, numerically robust homotopy algorithm for H/sub 2/ model reduction using the optimal projection equations" @default.
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- W2009017787 doi "https://doi.org/10.1109/cdc.1994.411102" @default.
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