In this paper the problem of constructing the minimum ℓ1 uncertainty model containing a finite set of assigned models is addressed. This problem is relevant to ℓ1 robust control design techniques, in order to minimize the size of the uncertainty set associated to the nominal plant. The problem is formulated as a (conditional) Chebyshev center problem and an algorithm for its solution is proposed. The algorithm converges in a finite number of steps showing computational efficiency for large size problems.

Casini, M., Garulli, A., & Vicino, A. (2008). Efficient computation of l1 uncertainty model from an impulse response set. AUTOMATICA, 44(10), 2570-2576 [10.1016/j.automatica.2008.02.006].

Efficient computation of l1 uncertainty model from an impulse response set

CASINI, MARCO;GARULLI, ANDREA;VICINO, ANTONIO
2008

Abstract

In this paper the problem of constructing the minimum ℓ1 uncertainty model containing a finite set of assigned models is addressed. This problem is relevant to ℓ1 robust control design techniques, in order to minimize the size of the uncertainty set associated to the nominal plant. The problem is formulated as a (conditional) Chebyshev center problem and an algorithm for its solution is proposed. The algorithm converges in a finite number of steps showing computational efficiency for large size problems.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/18591
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