ROBUST, REDUCED-ORDER, NONSTRICTLY PROPER STATE ESTIMATION VIA THE OPTIMAL PROJECTION EQUATIONS WITH PETERSEN-HOLLOT BOUNDS

被引:11
作者
HADDAD, WM
BERNSTEIN, DS
机构
[1] FLORIDA INST TECHNOL,DEPT MECH ENGN,MELBOURNE,FL 32901
[2] HARRIS CORP,DIV GOVT AEROSP SYST,MELBOURNE,FL 32902
关键词
Error bounds; Reduced-order state estimation; Robust Kalman filter;
D O I
10.1016/0167-6911(87)90072-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A state-estimation design problem involving parametric plant uncertainties is considered. An error bound suggested by recent work of Petersen and Hollot is utilized for guaranteeing robust estimation. Necessary conditions which generalize the optimal projection equations for reduced-order state estimation are used to characterize the estimator which minimizes the error bound. The design equations thus effectively serve as sufficient conditions for synthesizing robust estimators. An additional feature is the presence of a static estimation gain in conjunction with the dynamic (Kalman) estimator, i. e., a nonstrictly proper estimator. © 1987.
引用
收藏
页码:423 / 431
页数:9
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