Integrating Intelligent Pilot Modeling and Fidelity Metrics for Optimization of Motion Cueing Algorithms in Flight Simulator

This paper discusses the offline optimization issue of important parameters in the motion cueing algorithm, which is responsible for converting the motion status of the aircraft into the status of a six-degree-of-freedom motion platform to provide pilots with simulated force sensations. Traditionally, the optimization of the motion cueing algorithm relies on the subjective assessment of flight experts, which is not only time-consuming but also less accurate. This paper uses an intelligent pilot model to replace the traditional structural pilot model and introduces fidelity metrics from different flight missions to jointly optimize the key parameters in the motion cueing algorithm. The results show that this method can incorporate information from flight missions and digital pilots, optimizing the efficiency and accuracy within the motion cueing algorithm, although the complexity of the optimization has increased slightly.