Constrained Optimal Test Signal Design for Improved Prediction Error

This paper presents a new efficient methodology for the optimal design of discrete test signals in black-box dynamic nonlinear system identification. The approach is based on a new criterion which weights the parameter covariances with the magnitudes of output sensitivities both to reduce the parameter estimation error and also allow the optimization of the output fitness. Optimization using th…