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        Direct Yaw-Moment Control Evaluation of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer

        Author
        Geng, C.
        Mostefai, L.
        Denai, Mouloud
        Hori, Y.
        Attention
        2299/13291
        Abstract
        A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting
        Publication date
        2009-05
        Published in
        IEEE Transactions on Industrial Electronics
        Published version
        https://doi.org/10.1109/TIE.2009.2013737
        Other links
        http://hdl.handle.net/2299/13291
        Relations
        School of Physics, Engineering & Computer Science
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