An optimal model reduction method for closed-loop systems

An optimal model reduction method is presented for closed-loop systems. The procedure is an iterative one in that one endeavours to find the best reduced model of a given order so that the difference in the responses of the original closed-loop system and the closed-loop system with the reduced-order model is minimized. Optimal model reduction algorithms for a feedback system and a nonlinear feedback system are developed and examined. Illustrative examples are given to show the advantages of the optimal model reduction method for closed-loop systems presented.<<ETX>>