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Published October 1996 | Published
Journal Article Open

Model reduction of multidimensional and uncertain systems


Model reduction methods are presented for systems represented by a linear fractional transformation on a repeated scalar uncertainty structure. These methods involve a complete generalization of balanced realizations, balanced Gramians, and balanced truncation model reduction with guaranteed error bounds, based on solutions to a pair of linear matrix inequalities which generalize Lyapunov equations. The resulting reduction methods immediately apply to uncertainty simplification and state order reduction in the case of uncertain systems but also may be interpreted as state order reduction for multidimensional systems.

Additional Information

© 1996 IEEE. Manuscript received March 17, 1995; revised April 20, 1996. The authors are grateful to the reviewers for their helpful comments and suggestions.

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August 19, 2023
October 20, 2023