Intelligent adaptive control of bioreactors

Project members: R. Babuška

The goal of this research is the development and implementation of a robust self-tuning controller for fermentation processes. To ensure an optimal operating conditions, the pH value, the temperature and the dissolved oxygen concentration in the fermenter must be controlled within tight bounds. Ideally, the same control unit should be able to ensure the required performance for a whole variety of fermentation processes (different microorganisms), different scales (volume of one liter to several thousand liters) and throughout the entire process run. Figure 14 shows an experimental laboratory setup used in this project. The main control challenge is the fact that the dynamics of the system depend on the particular process type and scale and moreover are strongly time-varying, due to gradual changes in the process operating conditions.

Figure 14: Experimental laboratory setup (left) and the basic model-based adaptive control scheme (right).

Controllers with fixed parameters cannot fulfill these requirements. Self-tuning and adaptive control is applied to address the time-varying nature of the process. Among the different types of adaptive controllers (model-free, model-based, gain-scheduled, etc.), the model-based approach is pursued. The model is obtained through a carefully designed local identification experiment. Special attentions is paid to the robustness of the entire system in order to ensure safe and stable operation under all circumstances. The main contribution of this research is the development, implementation and experimental validation of a complete self-tuning control system. The robustness of the system is achieved by combining well-proven identification and control design methods with a supervisory fuzzy expert system. This research is being done a cooperation with Applikon Dependable Instruments B.V., Schiedam.