L-lysine Neuro-Dynamic Optimal Control
نویسندگان
چکیده
In this paper Neuro-dynamic programming (NDP) is proposed as an alternative to alleviate the “curse of dimensionality” of the Dynamic programming (DP) for optimal control of a fed-batch fermentation process in the L-lysine production. The most effective and cheapest method for the Llysine biosynthesis (in biological active form) is the microbiological method via a direct fermentation. In this paper an optimization method of the L-lysine production from strain Brevibacterium flavum 22LD is used and that is NDP. The results show that the quality of L-lysine enhances at the end of the process. The proposed method is particularly simple to implement and can be applied for on-line optimization.
منابع مشابه
Neuro-dynamic Optimal Control of a L-lysine Fed-batch Fermentation
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 is increased at the end of the process....
متن کاملNeuro-dynamic Programming for the Exploration of Unknown Graphs
In this paper, the problem of exploring stochastic graphs is addressed. The definition of the entropy related to the a-priori unknown parameters (the lengths of the a-priori unknown links) leads to the formulation of the problem as a stochastic optimal control one. The application of exact Dynamic Programming suffers the so-called curse of dimensionality. To overcome this drawback, an approxima...
متن کاملAdaptive dynamic programming-based optimal control of unknown nonaffine nonlinear discrete-time systems with proof of convergence
In this paper, a novel neuro-optimal control scheme is proposed for unknown nonaffine nonlinear discretetime systems by using adaptive dynamic programming (ADP) method. A neuro identifier is established by established RNN model, the ADP method is utilized to design the approximate optimal controller. Two neural networks (NNs) are used to implement the iterative algorithm. The convergence of the...
متن کاملOptimal Control of a Fed-batch Fermentation Process by Neuro-Dynamic Programming
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 time and procedure are decreased and ...
متن کاملNeuro-fuzzy Sliding Mode Controller Based on a Brushless Doubly Fed Induction Generator
The combination of neural networks and fuzzy controllers is considered as the most efficient approach for different functions approximation, and indicates their ability to control nonlinear dynamical systems. This paper presents a hybrid control strategy called Neuro-Fuzzy Sliding Mode Control (NFSMC) based on the Brushless Doubly fed Induction Generator (BDFIG). This replaces the sliding surfa...
متن کامل