Nonlinear model predictive control in a batch fermentator with state estimation

In this paper the use of nonlinear model predictive control of batch process is presented. The controller uses a continuous first principles model as the internal one. The process states are estimated using a moving horizon state estimator. The approach is illustrated by a simulation study of a batch process for the glucose fermentation to gluconic acid.