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We use the system |
We use the system |
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<math> |
<math> |
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+ | (E_0+s_1 E+s_2E_2+\ldots +s_pE_p)x=Bu(s_1,\ldots,s_p), \quad |
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− | E \frac{d{\bf x}}{dt}=A {\bf x}+B {\bf u}(t),</math> |
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+ | y=Cx, \quad \quad \quad \quad (1) |
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+ | </math> |
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+ | |||
<math> |
<math> |
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− | { |
+ | E \frac{dx(t)}{dt}=A x(t)+B u(t),</math> |
+ | <math> |
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+ | y(t)=Cx(t)+Du(t). |
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</math> |
</math> |
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Revision as of 17:13, 12 March 2013
The basic idea of almost all the model order reduction (MOR) methods is to
find a subspace which approximates the manifold where the state
vector Failed to parse (syntax error): {\bf x}(t)
resides. Afterwards, Failed to parse (syntax error): {\bf x}(t)
is approximated by a vector Failed to parse (syntax error): \tilde{\bf x}(t)
in $S_1$. The reduced model is produced by Petrov-Galerkin projection onto a subspace $S_2$, or by Galerkin projection onto the same subspace
.
We use the system
as an example to explain the basic idea. Assuming that an orthonormal
basis of the subspace
has been
found, then the approximation Failed to parse (syntax error): \tilde{\bf x}(t)
in
can be represented by
the basis as Failed to parse (syntax error): \tilde{\bf x}(t)=V{\bf z}(t)
. Therefore Failed to parse (syntax error): {\bf x}(t)
can be approximated by Failed to parse (syntax error): {\bf x}(t) \approx V{\bf z}(t)
. Here ${\bf z}$ is a vector
of length $q \ll n$.
Once Failed to parse (syntax error): {\bf z}(t) is computed, we can get an approximate solution Failed to parse (syntax error): \tilde{\bf x}(t)=V{\bf z}(t) for Failed to parse (syntax error): {\bf x}(t) . The vector Failed to parse (syntax error): {\bf z}(t) can be computed from the reduced model which is derived by the following two steps.