A Nikfetrat - Department of Electrical Engineering, Malek Ashtar University of Technology, Tehran, Iran.
V Babaeipour - Biotechnology Research Center, Malek Ashtar University of Technology, Tehran, Iran
A . R Vali - Department of Electrical Engineering, Malek Ashtar University of Technology, Tehran, Iran.

The paper presents a model-based predictive control strategy based on state space model for fed-batch biotechnological process. The process considered in this study is fed-batch cultivation of E. coli BL21 (DE3) [pET3aifnγ] under maximum attainable specific growth rate for producing γ-Interferon protein that maximum cell density (112 g/L DCW) and rhIFN-γ concentration (37g/L) after 16.5 h were achieved. Due to dynamic behavior of the fed-batch process and also subjecting the system to abrupt changes, the process behavior cannot be represented accurately bylinearizing around a single operating point so in this work model equation based on mass balance was linearized at every time step of the controller calculation. It is shown that the controller is capable to track the reference trajectories of biomass and substrate and also reject tolerate parameter variations.

E. coli, Fed-batch, model predictive control, State Space, rhIFN-γ