Guaranteed robust optimal experiment design for nonlinear dynamic systems

This paper is about optimal experiment design for uncertain nonlinear dynamic processes. We are interested in designing experiments which allow to identify the unknown states and parameters of a differential equation from noisy measurements. Here, unpredictable process noise or structural model-plant mismatches can be an additional complication. In this case, robustness aspects have to be taken into account as the experiment has to be planned under incomplete information. The paper discusses problem formulations and numerical solution approaches for this type of robust optimal experiment design problems under bounded uncertainties. The corresponding techniques are illustrated in the design of experiments for a fedbatch bioreactor.