OPTIMUM PERFORMANCE LEVELS FOR MINIMAX FILTERS, PREDICTORS AND SMOOTHERS

被引：70

作者：

BASAR, T

机构：

[1] UNIV ILLINOIS,DEPT ELECT & COMP ENGN,URBANA,IL 61801

[2] UNIV ILLINOIS,COORDINATED SCI LAB,URBANA,IL 61801

来源：

SYSTEMS & CONTROL LETTERS | 1991年 / 16卷 / 05期

关键词：

MINIMAX ESTIMATION; KALMAN FILTERING AND PREDICTION; H-INFINITY-SMOOTHING; ZERO-SUM GAMES;

D O I：

10.1016/0167-6911(91)90052-G

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For both discrete and continuous-time linear time-varying systems, we obtain the achievable performance levels for minimax filters, predictors and smoothers, in terms of the finite escape times of some related (discrete and continuous-time) Riccati equations. Our game-theoretic approach also yields an alternative derivation for the corresponding minimax estimators which were first obtained in [1]. They are all Bayes estimators with respect to particular Gaussian distributions, and admit recursive structures.

引用

页码：309 / 317

页数：9