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2.4 Krylov Subspace
Given a square matrix A q and a vector b q ,
the spanned by the vectors
A m 1
q
f
b q ;
A q b q ; ...;
b q g
is called a standard Krylov subspace of dimension m denoted
K m q f
A q ;
b q g
for each sub-matrix (Awais et al. 2007 ; Heyouni and Jbilou 2006 ):
K m q f A q ; b q g ¼span f b q ; A q b q ; ...; A m 1
b q g
ð
18
Þ
q
An effective reduced model in the form ( 2 ) by the projection onto the Krylov
subspace of the states matrices of system ( 1 ) is obtained. But there is another
method to generate the Krylov subspace, which is more ef
cient that called rational
Krylov subspace de
ned as :
Y
m q
j q ð
s 1 q I q Þ 1 b q ; ...;
s j q I q Þ 1 b q g
K m q f
A q ;
b q ;
s q g ¼
span
A q
A q
ð
19
Þ
where, s q ¼ ð
s 1 q ;
s 2 q ; ...;
s m q Þ
3 Dual Rational Krylov for Switched Linear System
In this section, the details of the Dual Rational Krylov algorithm for computing of
two projection matrices V r q and Z r q for each subsystem according to switching
signal q are brie
y recalled. Dual Rational Krylov is among the best approaches to
reduce the large-scale linear switched systems. It is easy to implemented, numer-
ically stable and to avoid the dif
fl
culties in the constructing of the two projections
matrices. V r q and Z r q are constructed column by column during the iteration process
using a Gram Schmidt techniques in orthogonalization procedure, such as the
condition of biorthogonalithy is satis
ed Z r q V r q ¼
I r q . Take a switched linear sys-
tem as a form ( 1 ) and assume that a sequence of expansion points
s r q g
is given, with r is the order of reduced subsystem. These expansion points are
interspersed. For each expansion point of each subsystem a two column vectors are
generated, i.e in the first iteration uses s 1 q , the second iteration uses s 2 q until
rth iteration.
The details of the Dual Rational Krylov algorithm for switched linear system can
be found in Table 1 (Antoulas 2009 ; Druskin and Simoncini 2011 ; Flagg et al.
2012 ; Zhanga et al. 2008 ).
The main steps of this method are:
f
s 1 q ;
s 2 q ; ...;
Step 1: Choose the interpolation points for each subsystem by the use of the
eigenvalues criterion (Gugercin 2008 ).
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