Enhancing MPC based Motion Cueing algorithm using modeFRONTIER

Eddi Valvason (Vi-Grade), Mattia Bruschetta (University of Padova)

Driving simulators are widely used in different applications: driver training, vehicle development, and medical studies. To fully exploit the potential of such devices, it is crucial to develop motion control strategies that generate realistic driving feelings. This has to be achieved while keeping the platform within its limited operation space. Such strategies are called motion cueing algorithms. A recent implementation of a motion cueing algorithm is based on Model Predictive Control technique. A distinctive feature of such approach is that it exploits an optimization procedure at each step based on a detailed model of the human vestibular system, and consequently differs from standard motion cueing strategies based on  washout filters. In this approach the MPC technique is used to compute the platform positions  that best reproduce the desired perception in the platform.