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This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...
This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and ...
The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...
Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previ ...
Institute of Electrical and Electronics Engineers2011
This paper aims to maximize the profitability of a set of brand SKUs stocked at a particular retailer by optimizing the number of facings for each product. Based on the past data, a set of variables such as retail price of different SKUs, linear footage th ...
In multivariate systems, when it comes to identifying actual operating conditions ranges, or optimal settings, the use of constrained optimization is often required. Among the different tools for the engineer to perform such optimization, designed experime ...
The purpose of this work is to analyse and study an efficient parametrization technique for a 3D shape optimization problem. After a brief review of the techniques and approaches already available in literature, we choose to use the Free Form Deformation p ...
The ability of a model-based real-time optimization scheme to converge to the plant optimum relies on the ability of the underlying process model to predict the plant's necessary conditions of optimality (NCO). These include the values and gradients of the ...
This paper presents a calibration framework for a precipitation-runoff model for flood prediction in a mesoscale Alpine basin with strongly anthropogenic discharges. The developed methodology addresses two classical hydrological calibration challenges: com ...
Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...