Receding Optimal Control of the Penicillin Fermentation Based on Boltzmann Machines

Based on dynamic neural network-Boltzmann machines, a new receding optimal control method of penicillin fermentation processes is proposed. First, according to the input and output data of the fed-batch fermentation processes, the subsection state-space models are built by system identification tools. Secondly, adopting the dynamic neural network-Boltzmann machine as an optimal controller, combining with the penicillin fermentation process and its state-space model, this paper structures the receding optimization closed loop. Simulation experiment results show that using this method the outcome concentration can increase thirty percent, and this control method is effectual