On the design of optimally informative dynamic experiments for model discrimination in multiresponse nonlinear situations
On the design of optimally informative dynamic experiments for model discrimination in multiresponse nonlinear situations
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DOI：
10.1021/ie0203025
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发表时间：
2003-04-02
影响因子：
4.2
通讯作者：
Asprey, SP
中科院分区：
文献类型：
--
作者：
Chen, BH;Asprey, SP
我们提出了一种新的确定最优信息动态实验的方法，目的是对几个通常由微分方程组和代数方程组(DAE)描述的相互竞争的多响应非线性结构动态模型进行模式识别。基于Buzzi-Ferraris和Forzatti(Chem.英语。SCI。1984，39，81)通过将试验设计问题重新表述为最优控制问题来计算动态输入轨迹。我们表明，通过考虑参数的不确定性，新的方法可以在区分一系列竞争的动态模型的能力方面提供显著的改进，而不是以前主要基于参数点估计设计动态实验的尝试，从而在不考虑不确定性的情况下最大化模型预测的分歧(Espie，D.M.；Macchietto，S.AIChE J.1989，35,223)。我们用一个相对简单但具有教育性的面包酵母发酵动态建模的例子来说明实验设计的概念，尽管这些方法足够通用，可以应用于其他建模练习。
We present a new method for determining optimally informative dynamic experiments for the purpose of model discrimination among several rival multiresponse nonlinear structured dynamic models generally described by systems of differential and algebraic equations (DAEs). A robust and efficient algorithm based on an extension to the dynamic case of the discrimination criterion put forth by Buzzi-Ferraris and Forzatti (Chem. Eng. Sci. 1984,39, 81) is developed to calculate dynamic input trajectories by reformulation of the experiment design problem as an optimal control problem. We show that the new approach, by taking parametric uncertainty into account, can provide significant improvements in the ability to distinguish among a series of rival dynamic models over previous attempts to design dynamic experiments primarily based on parameter point estimates and thus maximizes the divergence of the model predictions without regard for uncertainty (Espie, D. M.; Macchietto, S. AIChE J. 1989, 35, 223). We illustrate the experiment design concepts with a relatively simple, but pedagogical example of the dynamic modeling of the fermentation of baker's yeast, although the methods are general enough to be applied in other modeling exercises.