Optimization of microorganisms growth processes

Area of Science:

• Biotechnology and biochemical engineering
• Process control and optimization

Background:

• Microorganism growth is crucial in biotechnology but often inhibited by excess components.
• Inhibition leads to multiple equilibrium points, limiting access to optimal steady states.
• Dynamic control is essential for guiding systems from low microorganism concentrations to optimal states.

Purpose of the Study:

• To develop a dynamic control strategy for maximizing microorganism productivity in bioreactors.
• To address challenges posed by inhibited growth and multiple equilibrium points.
• To enhance the stability and accessibility of optimal steady states.

Main Methods:

• The study employs a two-part optimization strategy: steady-state optimization for maximum productivity and transient optimization for start-up.
• Transient optimization utilizes Pontryagin's maximum principle.
• The control law involves switching the dilution rate between minimum, maximum, and optimal values at specific times.

Main Results:

• The proposed control law effectively drives bioreactors to optimal steady states, maximizing productivity.
• This strategy significantly expands the stability region of the optimal equilibrium point.
• The control approach is efficient, simple, and broadly applicable to single biochemical reaction systems.

Conclusions:

• The developed dynamic control strategy enhances bioreactor productivity and stability.
• Its simplicity and generality make it suitable for real-world biotechnological applications.
• The method is independent of specific reaction kinetics, yield coefficients, or component numbers.