Run-to-run optimization via control of generalized constraints

Run-to-run Optimization via Control of Generalized Constraints

Run-to-run optimization methodologies exploit the repetitive nature of batch processes to determine the optimal operating policy in the presence of uncertainty. In this paper, a parsimonious parameterization of the inputs is used and the decision variables of the parameterization are updated on a run-to-run basis using a feedback control scheme which tracks signals that are invariant under unce...

Run-to-run Optimization via Constraint Control

Run-to-run optimization methodologies exploit the repetitive nature of batch processes to find the optimal operating policy in the presence of uncertainty. For the class of batch optimization problems where the solution is determined by terminal constraints, the update of the decision variables towards their optimal values is realized using a constraint control scheme. The methodology is adapte...

Run-to-Run Control in Semiconductor Manufacturing

Run-to-run Optimization of Batch Emulsion Polymerization

Run-to-run optimization exploits the repetitive nature of batch processes to adapt the operating policy in the presence of uncertainty. For problems where terminal constraints play a dominant role in the optimization, the system can be operated close to the optimum simply by satisfying terminal constraints. The input is parameterized by using the knowledge of the shape of the optimal solution a...

Modifier Adaptation for Run-to-Run Optimization of Transient Processes

Dynamic optimization can be used to determine optimal input profiles for dynamic processes. Due to plant-model mismatch and disturbances, the optimal inputs determined through model-based optimization will, in general, not be optimal for the plant. Modifier adaptation is a methodology that uses measurements to achieve optimality in the presence of uncertainty. Modifier-adaptation schemes have b...