Road profile estimation using an adaptive Youla- Kučera parametric observer: comparison to real profilers
Résumé
Road profile acts as a disturbance input to the vehicle dynamics and results in undesirable vibrations affecting the vehicle stability. A precise information of this data is mandatory for a better understanding of the vehicle dynamics behavior and active vehicle control systems design. However, direct measurements of the road profile are not trivial for technical and economical reasons, and thus alternative solutions are needed. This paper develops a novel observer, known as virtual sensor, suitable for real-time estimation of the road profile. The developed approach is carried on a quarter-car model and on measurements of the vehicle body. The road elevation is modeled as a sinusoidal disturbance signal acting on the vehicle system. Since this signal has unknown and time-varying characteristics, the proposed estimation method implements an adaptive control scheme based on the internal model principle and on the use of Youla-Kučera (YK) parametrization technique (also known as Q-parametrization). For performances assessment, estimations are comparatively evaluated with respect to measurements issued from Longitudinal Profile Analyzer (LPA) and Inertial Profiler (IP) instruments during experimental trials. The proposed method is also compared to the approach provided in (Doumiati et al. (2011)), where a stochastic Kalman filter is applied assuming a linear road model. Results show the effectiveness and pertinence of the present observation scheme.
Domaines
Automatique / RobotiqueOrigine | Fichiers produits par l'(les) auteur(s) |
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