Ellipsoidal state estimation based on sum of squares for non-linear systems with unknown but bounded noise

被引：5

作者：

Massioni, Paolo ^{[1
]}

Salnikov, Nikolay N. ^{[2
,3
]}

Scorletti, Gerard ^{[4
]}

机构：

[1] Univ Lyon, INSA Lyon, CNRS, Lab Ampere, F-69621 Villeurbanne, France

[2] Natl Acad Sci Ukraine, Inst Space Res, Kiev, Ukraine

[3] State Space Agcy Ukraine, Kiev, Ukraine

[4] Univ Lyon, Ecole Cent Lyon, CNRS, Lab Ampere, F-69134 Ecully, France

来源：

IET CONTROL THEORY AND APPLICATIONS | 2019年 / 13卷 / 12期

关键词：

polynomials; set theory; recursive estimation; linear systems; state estimation; least squares approximations; ellipsoidal state estimation; nonlinear systems; unknown but bounded noise; set-theoretic recursive state estimation; polynomial dynamics; ellipsoidal bounds; optimal ellipsoid; nonlinear system equations; linear system; MODELS; ERRORS;

D O I：

10.1049/iet-cta.2018.5072

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This brief concerns the set-theoretic recursive state estimation of non-linear systems with polynomial dynamics, making use of ellipsoidal bounds. The sum of squares approach is used to construct an optimal ellipsoid containing the intersection of sets obtained with the use of non-linear system equations and measurement equations. The properties of the proposed filter are illustrated with two examples, one concerning the simultaneous estimation of parameters and state of a linear system, and the other on the Euler equations of the rigid body rotational motion.

引用

页码：1955 / 1961

页数：7

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