Model reduction of uncertain interval systems using genetic algorithms

A GA-based approach is presented to derive a reduced model for a high-order interval system. To search for the optimal reduced model, we construct an aggregated error of the Bode envelopes between the original and reduced systems, subsequently minimized by a genetic algorithm. Impulse response energy of the interval systems is obtained to evaluate the performance of the reduced models.