| Generalized Model Based Design of Experiments DOE Criteria for Dynamic System Parameter Estimation | ||
| Yang Zhang, Department of Chemical Engineering, The University of Texas at Austin, 1 University Station; Mail Code C0400, Austin, TX 78712 and Thomas F. Edgar, Chemical Engineering, Dept. of Chem. Eng.,The University of Texas at Austin, 1 University Station Stop C0400, Austin, TX 78712 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. Extended Abstract Status: File Uploaded | ||