A robust fuzzy control design of yeast cultures in continuous bioreactors

In general, precise control of bioreactors is difficult due to the nonlinear behavior and the variations of parameters, which are always inevitable in the system. Earlier conventional techniques such as PID control, optimal control and so on, worked well for fungi that are with higher tolerance for the variations of the culture environment. However, these techniques are no longer effective in the face of cultivating new generation targets that is sensitive to the variations of the culture environment as mammalian cell, etc. Based on the reason depicted in the above, advanced control theories are highly desirable to apply to this bioreactor design problem that is under the effects of modeling uncertainties to improve its performance. One powerful control law that is combined with feedback linearization, adaptive fuzzy and optimal H _∞ control will be developed in this research for the above problem. It is well known the feedback linearization is a powerful technique and been widely applied to treat the tracking problem. These include the control of helicopters, high performance aircraft, industrial robots, and biomedical devices. However, all nonlinear control approaches require accurate knowledge of system dynamics. In practical situation, system dynamics are not always exactly known. Therefore, one method that can approach the unknown systems needed be used. It is famous that unknown systems can be approximated by the fuzzy logic systems that were thought as universal approximator for any nonlinear systems because unknown nonlinear systems can be approximated by fuzzy logic techniques to any desired accuracy. Generally, nonlinear bioreactor systems involve in modeling uncertainties. To handle this kind of system uncertainties, H _∞ control techniques have been proposed in recent years. Their applications to aerospace engineering include space station control, missile autopilot design, and spacecraft attitude control. From those applications, results reveal the strong performance robustness properties against system uncertainties and exogenous disturbances. By the combination of feedback linearization, fuzzy logic technique, and H_∞ control mentioned in the above, an adaptive fuzzy-based H_∞ control law has been successfully developed to treat the robust tracking problem of uncertain bioreactor systems.