The global approach in identification protocol optimization

The global identification approach is addressed. The local identification, which yields a solution represented by a point in a parametric space, is accompanied by uncertainty intervals for a given error level expressing a distance between the model and the true object. The iso-distance domain structure gives an indication of the relative distribution of information brought by the protocol on the model parameters. Optimal design of the protocol is also investigated. An application to a practical example shows the efficiency of the approach