On useful redundancy in experiment design for nonlinear system identification

In the paper, a formulation is proposed for optimal experiment design dedicated to the identification of nonlinear systems. In particular, a recently introduced redundancy property associated to dynamic systems related inverse problems is heavily exploited to guarantee global convergence. The paper considers general discrete-time nonlinear systems in which measurements are affected by bounded noise. An illustrative example is used to show the merits of the proposed approach.