The optimal design of dynamic experiments

A robust and efficient algorithm is developed to calculate dynamic inputs for optimal experimental designs. Different objective functions are presented to allow designs for both model discrimination and the improvement of parameter precision. Time‐varying inputs are calculated by reformulating the optimal design problem as an optimal control problem. This approach can provide large improvements in the ability to discriminate among a series of models, and then increase the accuracy of the resulting parameters.