INCLUSION OF MODEL UNCERTAINTY IN A COMPUTATIONAL FRAMEWORK FOR DYNAMIC OPERABILITY ASSESSMENT

This paper deals with the treatment of model uncertainty in a Q-parame trization framework for dynamic operability assessment. Structured non linear and/or time-varying model uncertainty is considered using the e l robust control theory of Khammash and Pearson (1991). In the case of unstructured model uncertainty, dynamic operability assessment is pos ed as a convex quadratic programming problem and solved efficiently us ing sparse matrix techniques. If the uncertainty is structured, the re sultant problem is nonconvex and is solved at present using a hybrid a pproach, with more sophisticated global optimization methods being inv estigated. The approach is applied to a multivariable distillation col umn containing all four performance limiting factors and the results a re discussed.