Development of a real-time Motion Cueing Algorithm based on Nonlinear Model Predictive Control techniques

The goal of this work is to develop a Motion Cueing Algorithm based on Model Predictive Control, which generate a trajectory that minimize a cost function, while not exceeding the simulator limits, exploiting the prediction of the future linear accelerations and angular velocities on the driver's head. In the last part of this thesis a proof of how the prediction window length affect the algorithm performances is given.