The focus of this investigation is the exploitation of knowledge of an ellipsoidal bound on system parameters for the identification of modeling uncertainty information vital to the H-infinity, robust control designer, a time to frequency domain uncertainty transformation. The characterizations of parametric uncertainty as coprime factor and additive perturbations to a nominal plant model are addressed in worst-case analyses. A Kharitonov type analysis provides sufficient conditions for the use of an additive plant perturbation uncertainty characterization. Original optimization results for the coprime factor perturbation enable the essential task of loopshaping to be conducted in the control design phase. A novel scheme is introduced to interpolate magnitude samples of the perturbation bounding function and is further developed into a technique for identification of reduced-order perturbation weightings, vital for practical control design. An example serves to illustrate the success of the developed techniques.