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A hierarchical framework based on Model Predictive Control (MPC) for autonomous vehicles is presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle while fulfilling various physical and design constraints. We start from the low-level active steering-controller presented in [3], [9] and integrate it with a high level trajectory...
A model predictive control (MPC) approach to active steering is presented for autonomous vehicle systems. The controller is designed to stabilize a vehicle along a desired path while rejecting wind gusts and fulfilling its physical constraints. Simulation results of a side wind rejection scenario and a double lane change maneuver on slippery surfaces show the benefits of the systematic control methodology...
This paper presents a survey of the recent research results of the authors in the field of modeling of automotive power train systems and components. The goal of the research is to propose simple and accurate power train models for controller design and to propose computationally efficient simulations. The modeling includes typical power train components such as electronic throttle, SI engine, torque...
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