DocumentCode
2212383
Title
Fault detection for an active vehicle suspension
Author
Fischer, Daniel ; Kaus, Eberhard ; Isermann, Rolf
Author_Institution
Inst. of Autom. Control, Darmstadt Univ. of Technol., Germany
Volume
5
fYear
2003
fDate
4-6 June 2003
Firstpage
4377
Abstract
After a short introduction into the topic of active vehicle suspension systems, a mathematical model of the used active vehicle suspension, which is presented in a test rig, is derived. It is shown how the unknown parameters can be obtained experimentally by parameter estimation. Using parameter estimation and LOLIMOT - a special type of neuronal networks, models of the active suspension are identified. These models are used for model based fault detection and identification, in order to obtain reliable knowledge of the system´s state. All results are shown for measurements from an active suspension on a test rig.
Keywords
fault diagnosis; neural nets; parameter estimation; road vehicles; LOLIMOT; active vehicle suspension system; fault detection; identification; local linear model tree; model based fault detection; neuronal networks; parameter estimation; parity equations; systems state; Control systems; Equations; Fault detection; Fault diagnosis; Frequency; Mechatronics; Parameter estimation; System testing; Vehicle dynamics; Vehicle safety;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2003. Proceedings of the 2003
ISSN
0743-1619
Print_ISBN
0-7803-7896-2
Type
conf
DOI
10.1109/ACC.2003.1240527
Filename
1240527
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