Abstract
This paper presents a new design metric for model-based Real-Time Optimization (RTO) system, named Extended Design Cost. Extended Design Cost is a systematic, comprehensive approach to evaluate different RTO design alternatives and is based on fundamental principles from optimization and statistics theory. It is defined as the loss in performance of the RTO system during some pre-specified evaluation period, due to design imperfections, and decomposed into three separate terms: Bias Cost. Transition Cost and Variance Cost. The proposed method is demonstrated using a chemical reactor optimization case study in which the adjustable parameters are selected.
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