ROBUST EXPERIMENT DESIGN VIA MAXIMIN OPTIMIZATION

When designing an experiment for estimating the parameters of a nonlinear model, the uncertainty in the nominal parameters has to be taken into account. For this a maximin methodology is used, where the parameters are assumed to belong to a known admissible domain, without any other hypothesis on their distribution. In some cases robust maximin design can be transformed into a simple problem of D-optimal design. When the maximin optimization problem cannot be avoided, an algorithmic procedure is proposed by which an approximate maximin optimal experiment can be designed at a reasonable cost.