Optimal Control of Cell Population Models with Uncertainties

Cell population dynamics can be described by cell population balance models. These models can be utilized for model-based control design but major aspects, which have not been captured in these models so far, are the regulation and mutational adaptation of the cells in long-term cultivations. Due to the stochastic nature of biological diversity and mutational adaptation, the impact on the cell dynamics is uncertain, and a quantization of these effects might not be repeatable. Therefore, it is evident for the control design to consider model-free optimization control schemes like Extremum Seeking and its partly model-free variations to maintain optimal reactor operation during long-term cultivations. The aim of this research project is to design these adaptive and flexible control schemes for the optimal control of cell population models with uncertainties. To achieve this, the convergence properties of the problem formulation are mathematically analyzed and tested in numerical simulations expected to lead to new results in this research area.

Faculty Supervisor:

Martin Guay

Student:

Partner:

Karlsruher Institut für Technologie

Discipline:

Engineering

Sector:

Education

University:

Queen's University

Program: