离散系统自寻最优降阶模型的一种新方法及应用

A NEW METHOD OF SEARCHING OPTIMAL REDUCED-ORDER MODEL FOR DISCRETE TIME SYSTEM(WITH APPLICATIONS)

本文提出了离散系统自寻最优降阶模型的一种新方法及应用.它是通过将误差多项式的系数设置为零使模型与系统的部分 M 参数及 H 参数相匹配,M 参数和 H 参数又是根据七种不同的误差积分指标由用户根据需要选定其中的任意一种,使这种误差积分指标最小而实现自寻最优的匹配,从而使获得的降阶模型接近于系统.就是说保持了系统的一定特性.这是一种合理的近似.根据这种方法以 PASCAL 语言编制成程序,在 PDP-11/23计算机上运行.以某个实际的计算机系统为例,进行了仿真和比较,论证了这种方法的正确性、可行性以及相当好的效果.这是一种效率高。易于实现 M 和 H 参数的最优匹配型,并易于理解的方法。

This paper presents a new method of searching optimal reduced-order model for a discrete time system.Anerror polynomial is defined,the coefficients of which indicate the difference at any instant between the sysem andthe model.It is shown how Markov parameters and H-parameters of the model can be matched with those of thesystem by setting error polynomial coefficients to zero.The H-parameters are proportional to the system timemoments.The searching of optimal matching of Markov and H-parameters are based on one of seven various in-tegral of the error performance index that minimizes it.This program is written in PASCAL language and runs on a PDP-11/23 minicomputer.By taking an actualcomputer system as an example we achieved simulation and comparison.It is shown that this method is quite cor-rect,feasible,efficient,and easily understandable.