Robust reduced-order modeling via the optimal projection equations with Peterson-Hollot bounds

An optimal reduced-order modeling problem with parametric plant uncertainty is considered. A model-reduction bound, suggested by recent work of I.R. Petersen and C.V. Hollot, is utilized for guaranteeing robust reduced-order modeling over a specified range of uncertain parameters. Necessary conditions which generalize the optimal projection equations for model reduction are used to characterize the reduced-order model which minimizes the model-reduction bound. The optimality equations thus effectively serve as sufficient conditions for characterizing robust reduced-order models