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Multivariable Optimization-Based Model Reduction
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DOI：10.1109/TAC.2009.2029402.png)
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Abstract
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In this technical note we introduce a multivariable extension of a recently proposed model reduction algorithm for linear time-invariant systems. Reduced models are found by solving a convex. optimization problem with Linear Matrix Inequality constraints given a state space model or frequency samples of a model. In order to illustrate the method we apply it to a large-scale model of a deformable mirror.
Keywords:
Multi-input-multi-output (MIMO)
single-input-single-output (SISO)
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