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PH control of penicillin fermentation process using predictive approach

Ashoori A., Moshiri B., Ramezani A., Bakhtiari M. R., Khaki-Sedigh A.

Systems Science

2009

Vol. 35, no 1

65-74

Bioprocesses which are involved in producing different pharmaceutical products may conveniently be classified according to the mode chosen for the process: either batch, fed-batch or continuous. From the control engineer's viewpoint they are fed-batch processes, which present the greatest challenge to get a pure product with a high concentration. Complicated dynamics, nonlinearity and non-stationarity make controlling them a very delicate task. pH control of bioreactors has been an interesting problem from both implementation and controller design points of view. This is particularly true if the complex microbial interactions yield significant nonlinear behavior. When this occurs, conventional control strategies may not succeed and more advanced strategies need to be suggested. This paper discusses model predictive control (MPC) based on a detailed unstructured model for penicillin production in a fed-batch fermentor. The approach used here is to use quadratic cost function for pH regulation, while taking into account control signal fluctuations in the optimization block. The result of applying the obtained controller and also its sensitivity to disturbance have been displayed and compared with the results of an auto-tuned PID controller used in previous works. The merit of this method is its low computational cost of solving the optimization problem, while leading to a closed form controller as well.

Modelling and identification of the respiratory control system

Noshiro M., Fukuoka Y., Nebuya S.

Biocybernetics and Biomedical Engineering

2000

Vol. 20, no. 3

93-108

Computer simulation using the models of the human gas exchange system showed that the PaC0(2) behavior of the Iinearized model agrees weII with those of other models in the range of 90 to 120 percent of normaI alveolar ventiIation. The pulmonary blood flow caIculated from the estimates in the Iinearized model of the CO(2) uptake system was significantIy correlated with the measured flow in the animaI experiment. This result indicates that the Iinearized model is adequate. A new method is proposed to-identify the nonIinear P(co2) controlIing system using a combination of a neural network and a polynomial NARMAX model. Computer simulation showed that the proposed method worked weIl.

Symulacja komputerowa wykorzystująca modele wymiany gazowej pokazuje, że zmienność PaCO(2) w modelu zlinearyzowanym odpowiada zmienności PaCO(2) w innych modelach, w zakresie zmian od 90 do 120% standardowej wentylacji pęcherzykowej. Perfuzja obliczana ze wskaźników w liniowym modelu zużycia CO(2) była dobrze skorelowana z płucnym przepływem krwi mierzonym podczas badań na zwierzętach. Fakty te wskazują na to, że model liniowy jest adekwatny. W pracy zaproponowano nową metodę do identyfikacji nieliniowego układu sterowania PaCO(2) wykorzystując kombinację sieci neuronowej i polynominalnego modelu NARMAX. Symulacja komputerowa wykazała, że zaproponowana metoda daje oczekiwane rezultaty.