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.
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