Observer-based adaptive control of a class of bioreactor processes

A stable adaptive observer-based control scheme, requiring on-line measurements of only one of the process states, is suggested for a class of nonlinearly-parametrized uncertain models encountered in bioreactor processes. In the first stage, a fixed observer-based controller is designed for the case when the process parameters are completely known, and, based on a suitable coordinate transformation suggested in this paper, it was shown that the resulting closed-loop system is stable, and that the output errors converge to zero asymptotically. Following that, the observer is used to design a stable adaptive controller in the case when the process growth model is of Monod type with unknown parameters. In both cases the stability and error convergence is demonstrated using suitably chosen Lyapunov functions, while the performance of the resulting closed-loop systems is evaluated through simulations.