Population Balance Model-based Dynamic Multiobjective Optimization of Yeast Cell Manufacturing

Abstract

Biological systems play a key role in many advanced manufacturing processes, of which many have interesting nonlinear dynamics. We investigate a continuous yeast cell manufacturing process that produces sustained oscillations in outputs under nominal conditions. Using a population balance model to perform dynamic optimization with multiple objectives and observability constraints, we quantify tradeoffs on the Pareto surface for varying the extent of process oscillations that the decision-maker deems tolerable (or desirable). Numerical optimal control design for oscillatory distributed parameter systems is discussed within the context of both dynamic optimization and on-line nonlinear model predictive control strategies.