Model Order Reduction with True Dominant Poles Preservation via Particles Swarm Optimization

A new computational technique for the reduction of multi-time scale systems is proposed in this paper. The reduction process is performed based on the dominant poles preservation in the reduced-order model. The true dominant poles are selected based on the highest contribution in redefined time moments and lowest contribution in redefined Markov parameters. Motivated by the singular perturbation approximation, obtaining the reduced-order model will be achieved by using the artificial intelligent method named particles swarm optimization. The potential of the proposed technique is observed when comparing its results with other recently published methods.