Application of Generalized Predictive Control to an Oscillatory Bioreactor

In this paper, an unforced oscillatory biological process has been studied and control of bioreactor outlet concentration has been considered. The unforced system shows oscillations for some special values of parameters. The system dynamic is chaotic when a forced perturbation on the feed concentration is imposed. Dynamic behavior of this chaotic reactor has been illustrated. The main objective is product concentration control and the adaptive generalized predictive control (AGPC) strategy has been proposed and its performance has been compared with that of a PI controller. The PI parameters are optimized based on an objective function via the genetic algorithm (GA). Results indicate that two controllers operate in an acceptable way, but the AGPC has a better performance as it was expected. In addition it has been shown that the AGPC is more robust to model mismatch.