Flatness-Based Vehicle Steering Control Strategy With SDRE Feedback Gains Tuned Via a Sensitivity Approach

This paper presents a feedback steering control strategy for a vehicle in an automatic driving context. Two main contributions in terms of control are highlighted. On the one hand, the automatic reference trajectories generation from geometric path constraints (obstacles). Thanks to the flatness property of the considered model, the longitudinal velocity will be controlled around a quasi-constant value while lateral and yaw dynamics targets will allow to avoid obstacles. On the other hand, a sensitivity-based methodology will be presented to choose the best possible gains parameterization in a state Riccati dependent equation (SDRE) feedback controller. Both direct and adjoint sensitivity methods are used, together with a dynamic inversion of the system, in order to optimize the performances of the controller. Obstacle avoiding simulation results will be validated and compared with other nonlinear optimal feedback controllers, from a realistic industrial simulator environment for vehicle dynamics

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