Optimal adaptive control schemes for PHB production in fed-batch fermentation of Ralstonia eutropha

• The robust and feasible feeding strategy for PHB production in a fed-batch bioprocess is investigated.
• The proposed optimal adaptive control strategy is determined by solving the constrained discrete-time optimization algorithm.
• Through Lyapunov stability analysis, the closed-loop stability is addressed.
• The simulations show that the satisfactory output tracking performance is achieved under the two-input control configuration.

A dynamic model for a fed-batch fermentation of Ralstonia eutropha for PHB production is presented. Based on the simplified kinetics, some of kinetic parameters are very sensitive to uncertainties. To develop the robust and feasible feeding strategy, the specific optimal adaptive control strategy is determined by solving the constrained discrete-time optimization algorithm using the genetic algorithm solver in Matlab. The proposed control methods are implemented to the feed flow manipulation with stepwise changes. Through Lyapunov stability analysis, the closed-loop stability regarding the state estimation errors and parametric uncertainties is investigated. Finally, simulations show that the satisfactory output tracking performance is achieved under the two-input control configuration.