Future reference prediction in model predictive control based driving simulators

The goal of a driving simulator is to produce an environment for a driver similar to the real driving scenario. Motion cueing algorithms are used to produce a realistic motion while respecting the workspace limitations and motion simulator boundaries. Model Predictive Control has become popular recently for motion cueing. However, in this control method, the optimization is based on a predefined constant future input trajectory while it is not a practical assumption. In this research, a method is proposed to predict the future reference based on the finite history of input. This method does not require the position trajectory to follow a specific road. Simulation results show the effectiveness of the proposed model predictive control method in terms of realistic motion sensation for a driver.