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A vehicle equipped with a front steer-by-wire device is considered and the related control design problem dealt with by using a yaw rate feedback structure. In order to effectively handle both the system non-linearities and the input constraints, a Non-linear Model Predictive Control (NMPC) technique is adopted. A novelty of the present paper is that the vehicle model employed by the NMPC algorithm is obtained from previously collected input/output data, using a Non-linear Set Membership (NSM) identification methodology. Since the NSM approach is able to provide a model with minimal worst-case identification error, improved robustness of the closed-loop system is obtained with respect to that of an NMPC law based on a physical vehicle model. Furthermore, the measure of the model uncertainty provided by the NSM approach allows one to perform a theoretical robust stability analysis of the closed-loop system. The effectiveness of the proposed technique is shown through numerical simulations of manoeuvres using a detailed vehicle model. [ABSTRACT FROM AUTHOR]

The paper investigates the use of a direct virtual sensor (DVS) to replace a physical sensor in a vehicle stability control system. A yaw control system is considered and the proposed solution can be particularly useful when a fault of the yaw rate physical sensor occurs. A DVS is a stable linear filter derived directly from input–output data, collected in a preliminary experiment. In this work, it is shown that, by using data collected in a closed-loop fashion, better DVS accuracy can be obtained with a reduced number of measured variables. Moreover, the robust stability of the closed-loop system employing a DVS is studied. The effectiveness of the presented results is shown through numerical simulations of harsh manoeuvres, performed using a detailed model of a vehicle equipped with an active front steering device. [ABSTRACT FROM AUTHOR]