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Difference between revisions of "Bilinear PMOR method"

(Created page with 'test')
 
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The model reduction method we present here is applicable to linear parameter-varying (LPV) systems of the form
test
 
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<center>
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<math>
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\dot{x}(t)=Ax(t) + \sum_{i=1}^d p_i(t)A_i x(t)+B_0u_0(t),\quad y(t)=Cx(t),
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</math>
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</center>
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  +
where
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<math>
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A,A_i \in \mathbb R^{n\times n}, B_0 \in \mathbb R^{n\times m}
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</math>
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and
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<math> C \in \mathbb R^{p\times n}.
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</math>
  +
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The main idea is that the structure of the above type of systems is quite similar to so-called bilinear control systems. Although belonging to the class of nonlinear control systems, the latter exhibit many features of linear time-invariant systems. In more detail, a bilinear control system is given as follows
  +
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<center>
  +
<math>
  +
\dot{x}(t)=Ax(t) + \sum_{i=1}^m N_i x(t) u_i(t) + B u(t),
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</math>
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</center>
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  +
where
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<math>
  +
A,N \in \mathbb R^{n\times n}, B \in \mathbb R^{n\times m}
  +
</math>
  +
and
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<math> C \in \mathbb R^{p\times n}.
  +
</math>

Revision as of 09:02, 6 December 2011

The model reduction method we present here is applicable to linear parameter-varying (LPV) systems of the form


\dot{x}(t)=Ax(t) + \sum_{i=1}^d p_i(t)A_i x(t)+B_0u_0(t),\quad y(t)=Cx(t),

where  
A,A_i \in \mathbb R^{n\times n}, B_0 \in \mathbb R^{n\times m}
and   C \in \mathbb R^{p\times n}.

The main idea is that the structure of the above type of systems is quite similar to so-called bilinear control systems. Although belonging to the class of nonlinear control systems, the latter exhibit many features of linear time-invariant systems. In more detail, a bilinear control system is given as follows


\dot{x}(t)=Ax(t) + \sum_{i=1}^m N_i x(t) u_i(t) + B u(t),

where  
A,N \in \mathbb R^{n\times n}, B \in \mathbb R^{n\times m}
and   C \in \mathbb R^{p\times n}.