Design Of Experiments (DOE) for parameter estimation in dynamic systems is receiving more attention from process system engineers. In this paper, a Generalized (G-) optimal criterion for model-based DOE is proposed that combines PCA with information matrix analysis. The G-optimal criterion is a general form that encompasses most widely-used optimal design criteria such as D-, E- and SV-optimal, and it can automatically choose the optimal objective function (criterion) to use for a specific DAE system. Engineering examples are used to validate the algorithms and assumptions. The advantages of G-optimal DOE include ease of reducing the scale of the optimization process by choosing parameter subsets to increase estimation accuracy and avoid an ill-conditioned information matrix.
