Neuro-dynamic Programming to Optimal Control of a Biotechnological Process

Abstract

Dynamic programming (DP) is an elegant way to solve problems related to optimization and optimal control of processes. DP, however, has one major drawback, namely the “curse of dimensionality”. To overcome this shortcoming, an approach called neuro-dynamic programming (NDP) has been developed. This approach solves the “curse of dimensionality” problem of DP. For this purpose, a neural network is used in NDP, which ignores the poor results of the utility criterion. In this way, the time for solving the specific task is significantly shortened. In this work, an NDP algorithm is presented for the optimal control of a fed-batch biotechnological process for the production of L-lysine by the strain Brevibacterium flavum 22LD. Application of the NDP algorithm ensures maximum productivity of the L-lysine.

Keywords

• optimal control
• dynamic programming
• neuro-dynamic programming
• fed-batch biotechnological processes
• l-lysine production
• brevibacterium flavum 22ld strain