Vehicle lateral dynamics estimation using unknown input observer
| Autor: | EL YOUSSFI, Naoufal, Oudghiri, Mohammed, El Bachtiri, Rachid |
|---|---|
| Přispěvatelé: | Université Sidi Mohamed Ben Abdellah (USMBA), Ecole Supérieure de Technologie de Fès (EST), École nationale des sciences appliquées de Fès = National School of Applied Sciences of Fez (ENSAF) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
quadratic function of Lyapunov
Computer Science::Systems and Control Vehicle Lateral Dynamics Takagi-Sugeno (T-S) fuzzy model [NLIN]Nonlinear Sciences [physics] Roll Motion Linear Matrix Inequalities (LMI) Unknown Input Observer (UIO) [SPI.AUTO]Engineering Sciences [physics]/Automatic [SPI.TRON]Engineering Sciences [physics]/Electronics |
| Zdroj: | The Second International Conference on Intelligent Computing in Data Sciences The Second International Conference on Intelligent Computing in Data Sciences, Oct 2018, Fez, Morocco |
| Popis: | International audience; This paper introduces an approach for estimating the parameters of the vehicle dynamics using a fuzzy Unknown Input Observer (UIO). The nonlinear model used has been deduced from the vehicle dynamics with a vision system is represented by a Takagi-Sugeno (T-S) fuzzy model in order to take into account the nonlinearities of the lateral forces. The convergence conditions of this observer are formulated as an optimization problem, subjected to constraints which are established using Lyapunov approach and expressed under Linear Matrix Inequalities (LMI). Thus, some simulations are performed on the nonlinear model of the vehicle lateral dynamics, with consideration of roll motion, that show a good efficiency of the proposed observer to estimate the system parameters, as well as the dynamic effect of the crosswind which is represented as an unknown input. |
| Databáze: | OpenAIRE |
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