Cost-Effective Estimation of Vehicle Lateral Tire-Road Forces and Sideslip Angle via Nonlinear Sampled-Data Observers: Theory and Experiments - Université Polytechnique des Hauts-de-France Accéder directement au contenu
Article Dans Une Revue IEEE/ASME Transactions on Mechatronics Année : 2024

Cost-Effective Estimation of Vehicle Lateral Tire-Road Forces and Sideslip Angle via Nonlinear Sampled-Data Observers: Theory and Experiments

Résumé

This article proposes a cost-effective method to jointly estimate the vehicle sideslip angle and lateral tire-road forces, which are crucial to improve the stability and performance of vehicle control systems. This method only requires the information from onboard sensors, readily available on mass-production vehicles. In particular, we consider the case of sampled asynchronous measurements, i.e. , the vehicle sensor signals used for observer design are transmitted at arbitrary and distinct times in a certain window bound over the vehicle networked control system. To this end, we propose a new data-sampled observer design, where the asynchronous phenomenon caused by the sampling process is explicitly taken into account via a linear parameter-varying framework. Based on an augmented Lyapunov--Krasovskii functional and specific relaxation techniques, the observer design conditions are derived to guarantee an ${L}_2$−gain performance for the discrete-continuous estimation error dynamics and a maximum allowable sampling period. The observer design is recast as a convex optimization problem, subject to linear matrix inequality (LMI) constraints, which can be efficiently resolved through conventional numerical solvers. The proposed sampled-data observer is experimentally evaluated with an autonomous vehicle under several dynamic driving scenarios, performed on a real test track
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Dates et versions

hal-04553950 , version 1 (22-04-2024)

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Anh-Tu Nguyen, Luciano Frezzatto, Thierry-Marie Guerra, Sébastien Delprat. Cost-Effective Estimation of Vehicle Lateral Tire-Road Forces and Sideslip Angle via Nonlinear Sampled-Data Observers: Theory and Experiments. IEEE/ASME Transactions on Mechatronics, In press, ⟨10.1109/TMECH.2024.3382777⟩. ⟨hal-04553950⟩
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