A Time Varying Model Predictive Motion Cueing Algorithm for Full Flight Simulator Upset Recovery Training

In order to improve the transfer of training, upset recovery training in full flight simulator need upgrade the motion cueing algorithm (MCA) due to updated training demands and limited workspace of motion platform. Existing algorithms are designed only for traditional flight tasks within the flight envelope instead of large amplitude tasks that experienced in upset recovery training. A new time varying model predictive control-based motion cueing algorithm is designed and developed to balance the angular rate and linear acceleration sensation effect with previewed available motion workspace optimization. The different control objectives in the stages of upset recovery are considered in the optimization algorithm design. Both switched motion perception model and variable weights in cost function are incorporated in the controller with the scheduling parameters such as motion platform and simulated flight states. Simulation results of a typical pitch upset scenarios show that the proposed algorithm has better motion perception replication capability than the traditional MCA in the upset recovery training.