Integrated design and control using a dynamic inversely controlled process model

The profitability of chemical processes depends on their design and control. If the process design is fixed, there is little room left to improve control performance. Many commentators suggest design and control should be integrated. Nevertheless, the integrated problem is highly complex and intractable. This article proposes an optimization framework using a dynamic inversely controlled process model. The combinatorial complexities associated with the controllers are disentangled from the formulation, but the process and its control structure are still designed simultaneously. The new framework utilizes a multi-objective function to explore the trade-off between process and control objectives. The proposed optimization framework is demonstrated on a case study from the literature. Two parallel solving strategies are applied, and their implementations are explained. They are dynamic optimization based on (i) sequential integration and (ii) full discretization. The proposed integrated design and control optimization framework successfully captured the trade-off between control and process objectives.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► A novel optimization framework for integrated design and control is introduced. ► The problem complexity is reduced using a dynamic inversely controlled process model. ► The inversely controlled process model implies an assumption of perfect control. ► The complexity of controller design is disentangled from the problem formulation. ► The proposed method is benchmarked on a case study from literature.