LOW SENSITIVITY FILTERS FOR STATE ESTIMATION IN PRESENCE OF LARGE PARAMETER UNCERTAINTIES

被引：18

作者：

DAPPOLITO, JA

HUTCHINSON, CE

机构：

[1] Dept. of Elec. Engrg., University of Massachusetts, Amherst, Mass.

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1969年 / AC14卷 / 03期

关键词：

D O I：

10.1109/TAC.1969.1099185

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Three minimax sensitivity criteria are used to synthesize filters for estimating the state of a simple first-order plant when large uncertainties in dynamic and/or statistical parameters of the plant and measurement system are present. Two design examples involving unknown plant bandwidth and unknown plant input noise covariance are worked out in detail. Graphical comparison of the error performance of the three minimax sensitivity filters with that of the optimal filter is presented for each case. © 1969 IEEE. All rights reserved.

引用

页码：310 / +

页数：1