Towards on-line model-based design of experiments

Abstract Model-based experiment design aims at detecting a set of experimental conditions yielding the most informative process data to be used for the estimation of the process model parameters. In this paper, a novel on-line strategy for the optimal model-based re-design of experiments is presented and discussed. The novel technique allows the dynamic update of the control variable profiles while an experiment is still running, and can embody a dynamic investigation of different directions of information through the adoption of modified design criteria. A case study illustrates the benefits of the new approach when compared to a conventional design.