Abstract This paper presents the simulation results of applying the robust multivariate linear quadratic Gaussian/loop transfer recovery (LQG/LTR) control design methodology to a nonlinear bacterial growth system. The growth system is modeled in state space format containing inde-pendent white noise processes in the system equations. The objective is to design a control system that maintain stable bioreactor operation at a chosen set point in the face of external disturbances and internal modeling uncertainty. The nonlinear system is first linearized around a nominal operating set point. Then, a LQG controller is designed for this linearized system. The control design is carried out by using an expert system called CASCADE, developed at the University of Tennessee. Computer simulations, using the original non-linear system equations in generating the “raw” measurements, demonstrate the closed-loop system is robust . This robustness of the control design approach has wide application potential to industrial scale production of biochemicals using bioreactor systems.
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