Efficient control of fed-batch baker's yeast cultivation based on neural network

A neural network control strategy for fed-batch baker's yeast cultivation was considered in the present work. A non-linear single-input single-output system was identified by the neural network, where the input variable was the feed rate of glucose and the output variable was the ethanol concentration. The predictive control law based on the optimal performance index was introduced into the neural network control in order to obtain good quality of control. The training of the neural network was done by using the data of on-off control. The experimental results show that it could control the ethanol concentration at the setpoint effectively.