DocumentCode
3548800
Title
Unknown Input Detection Using Receding Horizon Approach
Author
Kulcsár, Balázs ; Bokor, József
Author_Institution
Dept. of Transp. Autom., Budapest Univ. of Technol. & Econ.
fYear
2005
fDate
27-29 June 2005
Firstpage
423
Lastpage
428
Abstract
The paper offers the possibility of the design of unknown input detection for dynamic systems under external noise effect. The presented geometric based fundamental problem in residual generation (FPRG) method uses on the one hand the Kalman filtering and on the other hand the moving horizon estimation (MHE) when stochastic noise on the input and on the output, with additive failure directions, are presents. The paper combines the optimal Kalman and MHE method with geometric based unknown input observer strategy. The MHE solution makes to treat constraints during the estimation process possible. A numerical example supports the necessity of constrained unknown input estimation
Keywords
Kalman filters; fault location; noise; observers; time-varying systems; Kalman filtering; dynamic system; external noise effect; fundamental problem in residual generation method; moving horizon estimation; receding horizon approach; stochastic noise; unknown input detection; unknown input observer strategy; Additive noise; Automation; Control systems; Fault detection; Kalman filters; Predictive control; Predictive models; Space technology; Stability; State estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation
Conference_Location
Limassol
ISSN
2158-9860
Print_ISBN
0-7803-8936-0
Type
conf
DOI
10.1109/.2005.1467052
Filename
1467052
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