Title :
An algorithm for model reduction of large-scale systems via equality constrained least squares
Author :
An, Yu´e ; Gu, Chuanqing
Author_Institution :
Dept. of Math., Shanghai Univ., Shanghai, China
Abstract :
A new SVD-Krylov based method is proposed, which is equivalent to compute an equality constrained leastsquares problem. The reduced model matches the first r + i Markov parameters of the full order model. Based on the rational equality constrained least-squares method, an iterative algorithm for H2 model reduction is prensented. Moreover, both algorithms of IRKA ( An Iterative Rational Krylov Algorithm)and ISRK(An iterative SVD-rational Krylov based model reduction method) turns out to be two special cases of the proposed algorithm. The algorithm is numerically effective and suited for large-scale problem, which can be verified in the numerical examples.
Keywords :
Markov processes; iterative methods; least squares approximations; singular value decomposition; H2 model reduction; Markov parameters; SVD-Krylov based method; equality constrained least squares; full order model; iterative algorithm; iterative rational Krylov algorithm; large-scale systems; singular value decomposition; Iterative methods; Least squares approximation; Markov processes; Numerical models; Numerical stability; Reduced order systems;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583128