A new approach for robust model predictive control of biological production processes

This paper presents an approach for robust open-loop and closed-loop control of biological production processes described by models with parameter uncertainties. The approach leads to trajectories that show small variations of the product amount if uncertain parameters and uncertain initial conditions are present. The algorithm utilizes a second order approximation to calculate the first two statistical moments of the system's output as a function of the stochastic system's state and uncertain model parameters.