Studies on on-line bioreactor identification. I. Theory

Area of Science:

• Biochemical Engineering
• Process Systems Engineering
• Biotechnology

Background:

• Accurate real-time state estimation is crucial for optimizing biochemical reactor performance and control.
• Existing methods often struggle with process noise, measurement inaccuracies, and the need for complex kinetic models.
• Integrating elemental and macroscopic balances with advanced estimation techniques offers a potential solution.

Purpose of the Study:

• To develop an integrated, on-line approach for estimating the state of biochemical reactors.
• To accurately determine total growth rate and unknown culture parameters using real-time measurements.
• To provide a flexible framework for incorporating new sensors and improving estimation accuracy.

Main Methods:

• Utilizing elemental and macroscopic balances for total growth rate determination.
• Employing state-of-the-art estimation techniques to filter noise and estimate state variables.
• Developing a flexible framework adaptable to new sensor availability.

Main Results:

• Successful on-line estimation of biochemical reactor states, including growth rates and parameters.
• Effective elimination of process and measurement noise under both steady-state and transient conditions.
• Demonstrated flexibility in incorporating new sensors for enhanced variable estimation.

Conclusions:

• The presented integrated approach provides robust and accurate on-line state estimation for biochemical reactors.
• The method's independence from growth kinetics models and its noise-handling capabilities are significant advantages.
• Estimated state variables facilitate the development of adaptive optimal control and microbial culture studies.