Tatiana Ilkova

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In this paper the method for optimal control of a fermentation process is presented, that is based on an approach for optimal control-Neuro-dynamic programming. For this aim the approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this approach computing(More)
A fed-batch fermentation process is examined in this paper for experimental and further dynamic optimization. The static optimization is developed for to be found out the optimal initial concentrations of the basic biochemical variables – biomass, substrate and substrate in the feeding solution. For the static optimization of the process the method of(More)
In this work a neuro-fuzzy based model of a whey batch fermentation process by a strain Kluyveromyces marxianus var. lactis MC5 is presented. A three-layered neuro-fuzzy network is realized. The simulation results are compared with conventional models (based on mass balance and differential equations). The neuro-fuzzy model provides a better fitness and(More)
In this paper is developed an optimal control of fermentation process of L-lysine production with the Neuro-dynamic programming theory. A approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this optimization procedure the quantity L-lysine productions(More)
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