Designing positive excitation signals for the safe identification of nonlinear integrating systems

Designing identification experiments for nonlinear systems that can only be excited by positive input signals is a challenge. Large excitations improve the signal-to-noise ratio but risk deviating the system from the desired operating point due to their increased mean. To address this, we propose an algorithm that minimizes the integral of the perturbation, balancing the signal-to-noise ratio and the deviation from the target. We validate this approach with a nonlinear diffusive simulation, which is illustrative for fusion energy applications.