Robust optimal control for the maximization of design space

A commonly applied procedure in the pharmaceutical industry is to determine the maximum allowable set of uncertain parameters-called the design space-that guarantees that the product quality attributes obtained by a manufacturing process are within the specific limits. Design spaces in industry are constructed without considering the effects of process dynamics or feedback control, which results in design spaces that poorly characterize the real operations. This paper presented approaches for determining the design space for a dynamic state-space model with linear fractional uncertainties and for synthesizing a linear feedback control law for a set of ellipsoidal quality attributes by using invariant set theory. The proposed method is illustrated in a simulation example.