H/sub 2/ and/or H/sub /spl infin//-norm model reduction of uncertain discrete-time systems

This paper addresses the problem of model reduction for uncertain discrete-time systems with convex bounded (polytope type) uncertainty. A reduced order precisely known model is obtained in such a way that the H/sub 2/ and/or the H/sub /spl infin// guaranteed norm of the error between the original (uncertain) system and the reduced one is minimized. The optimization problems are formulated in terms of coupled (nonconvex) linear matrix inequalities, being solved through iterative algorithms. Examples illustrate the results.