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
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;
Conference_Titel :
American Control Conference, 2003. Proceedings of the 2003
Print_ISBN :
0-7803-7896-2
DOI :
10.1109/ACC.2003.1240527