Model predictive controller for biodegradable polyhydroxyalkanoate production in fed-batch culture

Area of Science:

• Biotechnology and Biochemical Engineering
• Polymer Science
• Control Systems Engineering

Background:

• Conventional controllers struggle with large biosensor sampling intervals, leading to concentration overshoots.
• Metabolic flux distribution control is key for optimizing biopolymer production.
• Accurate control of monomer composition is crucial for desired polymer properties.

Purpose of the Study:

• To develop a model predictive controller (MPC) integrated with a metabolic reaction model for P(HB-co-HV) production.
• To precisely control ethanol and n-pentanol concentrations and the mole fraction of 3HV units.
• To enhance the production yield of the biodegradable copolyester P(HB-co-HV).

Main Methods:

• Implemented a single-input, single-output (SISO) MPC for ethanol control during the growth phase.
• Developed a multi-input, multi-output (MIMO) MPC for dual alcohol control during the production phase.
• Estimated specific ethanol consumption rates using MPC and historical concentration data.

Main Results:

• MPC demonstrated superior control of ethanol and n-pentanol concentrations compared to PI and feedforward/feedback controllers.
• Optimized weighting parameters for MPC noise filters through simulations and experiments.
• Achieved maximized P(HB-co-HV) production at a target mole fraction of 3HV units.

Conclusions:

• MPC offers a robust solution for managing complex fermentation processes.
• The developed controller enables precise regulation of substrate concentrations and monomer composition.
• This approach significantly enhances the yield of P(HB-co-HV), a valuable biodegradable polymer.