Estimation for Nonlinear Dynamical Systems over Packet-Dropping Networks

Author

Jin, Zhipu ; Ko, Chih-Kai ; Murray, Richard M.

Author_Institution

Univ. of California, Los Angeles

fYear

2007

fDate

9-13 July 2007

Firstpage

5037

Lastpage

5042

Abstract

Two approaches, extended Kalman filter (EKF) and moving horizon estimation (MHE), are discussed for state estimation for nonlinear dynamical systems over packet-dropping networks. For EKF, we provide sufficient conditions that guarantee a bounded EKF error covariance. For MHE, a natural scheme on organizing the finite horizon window is proposed to handle intermittent observations. A nonlinear programming software package, SNOPT, is employed in MHE and the formulation for constraints is discussed in detail. Examples and simulation results are presented.

Keywords

Kalman filters; distributed control; nonlinear dynamical systems; nonlinear programming; software packages; state estimation; SNOPT; extended Kalman filter; moving horizon estimation; networked control systems; nonlinear dynamical systems; nonlinear programming software package; packet-dropping networks; state estimation; Communication networks; Communication system control; Control systems; Decoding; Estimation error; Networked control systems; Nonlinear dynamical systems; Stability; State estimation; Sufficient conditions; State estimation; extended Kalman filter; moving horizon estimation; nonlinear dynamical systems; packet-dropping networks;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2007. ACC '07

Conference_Location

New York, NY

ISSN

0743-1619

Print_ISBN

1-4244-0988-8

Electronic_ISBN

0743-1619

Type

conf

DOI

10.1109/ACC.2007.4283063

Filename

4283063