In this paper, we examine the problem of determining the worst-case H2 performance of a control system subject to linear, time-invariant uncertainties. We derive upper bounds on the performance, based on the theory of stability multipliers and the solution of an original optimal control problem. We address the numerical issues raised by the resulting computational problems: in particular, we show that newly developed interior-point convex optimization methods, combined with Linear Matrix Inequalities apply very well to the fast and accurate solution of these problems. The new results compare favorably with prior ones.
|Original language||English (US)|
|Title of host publication||Proceedings of the IEEE Conference on Decision and Control|
|Publisher||IEEEPiscataway, NJ, United States|
|Number of pages||6|
|State||Published - Dec 1 1994|