State estimation for optimal control of a nonlinear system

Two estimation techniques, the extended Kalman filter (EKF) and the iterative extended Kalman filter (IEKF), have been applied to a nonlinear time-varying system that has nonmeasurable state variables. An iterative solution to a fed-batch fermentation process is reported using the EKF based on measurements of the oxygen and carbon dioxide concentrations. The results demonstrate that this estimation technique can be successfully applied to complex biological processes. If the nonlinearities of these systems are sufficiently important or if a long delay in the estimation cannot be permitted for a particular process, then the IEKF can be selected