Model Reduction for Linear Parameter-Dependent Systems
نویسنده
چکیده
The paper considers the problem of model reduction for a class of linear parameterdependent (LPD) systems. Three model reduction approaches: balanced truncation, balanced LQG truncation and gain-scheduledH∞ model reduction, are presented to reduce the dimension of LPD systems. For the former two approaches, conditions to proceed the reduction are given in terms of a finite number of linear matrix inequalities (LMIs); while the latter one involves LMIs with some additional rank constraint.
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