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Difference between revisions of "Projection based MOR"

Line 7: Line 7:
 
We use the system
 
We use the system
 
<math>
 
<math>
E \frac{d{\bf x}}{dt}=A {\bf x}+B {\bf u}(t), \quad
+
E \frac{d{\bf x}}{dt}=A {\bf x}+B {\bf u}(t),</math>
  +
<math>
 
{\bf y}(t)=C{\bf x}+D{\bf u}(t).
 
{\bf y}(t)=C{\bf x}+D{\bf u}(t).
 
</math>
 
</math>

Revision as of 17:12, 12 March 2013


The basic idea of almost all the model order reduction (MOR) methods is to find a subspace S_1 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 S_1.

We use the system Failed to parse (syntax error): E \frac{d{\bf x}}{dt}=A {\bf x}+B {\bf u}(t), Failed to parse (syntax error): {\bf y}(t)=C{\bf x}+D{\bf u}(t).

as an example to explain the basic idea. Assuming that an orthonormal basis V=(v_1,v_2, \ldots, v_q) of the subspace S_1 has been found, then the approximation Failed to parse (syntax error): \tilde{\bf x}(t) in S_1 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.