LMI-based state estimator design for discrete-time stochastic systems with quadratic sum constraints

Author

Yaz, Edwin Engin ; Yaz, Yvonne Ilke

Author_Institution

Dept. of Electr. Eng., Arkansas Univ., Fayetteville, AR, USA

Volume

1

fYear

2001

fDate

2001

Firstpage

75

Abstract

A general class of discrete-time uncertain nonlinear stochastic systems with quadratic sum constraints is considered. A linear full-order state estimator design is presented for various estimation error performance criteria in a unified framework. These performance criteria include guaranteed-cost suboptimal versions of estimation objectives like H₂, H_∞, stochastic passivity, etc. The design of linear state estimators that satisfy these criteria are given using a common linear matrix inequality (LMI) formulation

Keywords

H^∞ control; constraint theory; control system synthesis; discrete time systems; errors; matrix algebra; nonlinear systems; performance index; state estimation; stochastic systems; suboptimal control; uncertain systems; H_∞ control; H₂ control; discrete-time uncertain nonlinear stochastic systems; estimation error performance criteria; guaranteed-cost suboptimal estimation objectives; linear full-order state estimator design; linear matrix inequalities; quadratic sum constraints; state estimator design; stochastic passivity; Educational institutions; Equations; Estimation error; Linear matrix inequalities; Mathematics; Noise measurement; Power system modeling; State estimation; Stochastic processes; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2001. Proceedings of the 2001

Conference_Location

Arlington, VA

ISSN

0743-1619

Print_ISBN

0-7803-6495-3

Type

conf

DOI

10.1109/ACC.2001.945517

Filename

945517