SOME MODEL ORDER REDUCTION METHODS FOR UNSTABLE SYSTEM BASED ON BALANCED TRUNCATION ALGORITHM

Abstract

In this paper, we introduce and compare some model order reduction methods for unstable system based on balanced truncation algorithm. The results show that Zhou's balanced algorithm gives the best reduction result in the overall frequency range. The LQG balanced algorithm has the largest order reduction error in three order reduction algorithms. Zhou's equalization algorithm has the smallest order reduction error in the three algorithms. The simulated results show the advantages, disadvantages and the applicability of the reduction methods.