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Dynamic and Neuro-Dynamic Optimization of a Fed-Batch Fermentation Process

机译:分批补料发酵过程的动态和神经动力学优化

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A fed-batch fermentation process is examined in this paper for experimental and further dynamic optimization. The optimization of the initial process conditions is developed for to be found out the optimal initial concentrations of the basic biochemical variables - biomass, substrate and feed substrate concentration. For this aim, the method of dynamic programming is used. After that, these initial values are used for the dynamic optimization carried out by neuro-dynamic programming. The general advantage of this method is that the number of the iterations in the cost approximation part is decreased.
机译:本文对分批补料发酵过程进行了实验和进一步的动态优化。为了找到基本生化变量的最佳初始浓度(生物质,底物和饲料底物浓度),开发了初始工艺条件的优化。为此目的,使用动态编程的方法。之后,将这些初始值用于通过神经动力学编程进行的动力学优化。该方法的一般优点是减少了成本近似部分中的迭代次数。

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