13th European Workshop on Advanced Control and Diagnosis | |
Tire Force Estimation using a Proportional Integral Observer | |
Farhat, Ahmad^1 ; Koenig, Damien^1 ; Hernandez-Alcantara, Diana^2 ; Morales-Menendez, Ruben^2 | |
Gipsa-Lab INPG 11 Rue des Mathématiques, Grenoble Campus BP 46, Saint Martin d'Hères Cedex | |
38, 402, France^1 | |
Tecnológico de Monterrey, School of Engineering and Sciences, Av Eugenio Garza Sada # 2501, Col. Tecnológico 64, Nuevo León Monterrey | |
849, Mexico^2 | |
关键词: Disturbance attenuation; Multi-objective problem; Multiple Lyapunov function; Proportional integral observer; Proportional-integral observers; Residual sensitivities; Robust fault detection; Uncertain switched systems; | |
Others : https://iopscience.iop.org/article/10.1088/1742-6596/783/1/012014/pdf DOI : 10.1088/1742-6596/783/1/012014 |
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来源: IOP | |
【 摘 要 】
This paper addresses a method for detecting critical stability situations in the lateral vehicle dynamics by estimating the non-linear part of the tire forces. These forces indicate the road holding performance of the vehicle. The estimation method is based on a robust fault detection and estimation approach which minimize the disturbance and uncertainties to residual sensitivity. It consists in the design of a Proportional Integral Observer (PIO), while minimizing the well known H∞norm for the worst case uncertainties and disturbance attenuation, and combining a transient response specification. This multi-objective problem is formulated as a Linear Matrix Inequalities (LMI) feasibility problem where a cost function subject to LMI constraints is minimized. This approach is employed to generate a set of switched robust observers for uncertain switched systems, where the convergence of the observer is ensured using a Multiple Lyapunov Function (MLF). Whilst the forces to be estimated can not be physically measured, a simulation scenario with CarSimTMis presented to illustrate the developed method.
【 预 览 】
Files | Size | Format | View |
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Tire Force Estimation using a Proportional Integral Observer | 1012KB | download |