Control effectiveness estimation using an adaptive Kalman estimator

Author

Wu, N. Eva ; Zhang, Youmin ; Zhou, Kemin

Author_Institution

Dept. of Electr. Eng., State Univ. of New York, Binghamton, NY, USA

fYear

1998

fDate

14-17 Sep 1998

Firstpage

181

Lastpage

186

Abstract

In this paper, an adaptive Kalman filtering algorithm is exploited for use to estimate the abrupt reduction of control effectiveness in dynamic systems. Control effectiveness factors are used to quantify faults entering control systems through actuators. A set of covariance-dependent forgetting factors is introduced into the filtering algorithm. As a result, the change in the control effectiveness is accentuated to help achieve a more accurate estimate more rapidly. The algorithm is applied to an aircraft model for the identification of impairment in its control surfaces

Keywords

adaptive Kalman filters; aircraft control; control system analysis; covariance matrices; discrete time systems; linear systems; parameter estimation; adaptive Kalman filter; aircraft model; control effectiveness estimation; covariance matrix; discrete time systems; dynamic systems; filtering; forgetting factors; identification; linear systems; Adaptive control; Control systems; Electric variables measurement; Fault diagnosis; Filtering algorithms; Kalman filters; Leg; Programmable control; State estimation; US Department of Defense;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control (ISIC), 1998. Held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Proceedings

Conference_Location

Gaithersburg, MD

ISSN

2158-9860

Print_ISBN

0-7803-4423-5

Type

conf

DOI

10.1109/ISIC.1998.713657

Filename

713657