A Gramian-based approach to model reduction for uncertain systems

Publication Type:
Conference Proceeding
Proceedings of the IEEE Conference on Decision and Control, 2007, pp. 4373 - 4378
Issue Date:
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The paper considers the problem of model reduction for a class of uncertain systems with structured norm bounded uncertainty. The paper introduces controllability and observability Gramians in terms of certain parameterized algebraic Riccati inequalities. This enables a balanced trun-cation model reduction procedure for uncertain systems to be presented. Error bounds for this model reduction procedure are derived. The paper also investigates H ∞ model reduction for uncertain systems. The solution to this problem is shown to involve constructing the underlying Gramians satisfying a certain rank constraint. ©2007 IEEE.
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