(289a) Generalized Model Based Design of Experiments DOE Criteria for Dynamic System Parameter Estimation

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.