文章基本信息

标题：A Two-loop Optimization Strategy for Multi-objective Optimal Experimental Design
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作者：Hui Yu ; Hong Yue ; Peter Halling 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：7
页码：803-808
DOI：10.1016/j.ifacol.2016.07.288
语种：English
出版社：Elsevier
摘要：A new strategy of optimal experimental design (OED) is proposed for a kinetically controlled synthesis system by considering both the observation design and the input design. The observation design that combines sampling scheduling and measurement set selection is treated as a single optimization problem arranged in the inner loop, while the optimization of the input intensities is conducted in the outer loop. This multi-objective dynamic optimization problem is solved via the integration of the particle swarm algorithm (for the outer loop) and the interior-point method (for the inner loop). Numerical studies demonstrate the efficiency of this optimization strategy and show the effectiveness of this integrated OED in reducing parameter estimation uncertainties. In addition, process optimization of the case study enzyme reaction system is investigated with the aim to obtain the maximum production rate by taking into account of the experimental cost.
关键词：Multi-objective optimal experimental design (OED)process optimizationobservation strategyinput designparameter estimationenzyme reaction system