Research On Integrated Motion Cueing Algorithm For Upset Prevention And Recovery Training In Flight Simulator

According to flight accident statistics, Loss-of-Control(LOC) has surpassed Controlled-Flightinto-Terrain(CFIT) to become the leading contributor of worldwide commercial aircraft fatalities in recent years. With the widespread use of Ground Proximity Warning System(GPWS), the frequency of CFIT accidents have been significantly reduced. In contrast, there is no single and mature technology means to prevent LOC. Flight simulator is currently the only safe, low-cost and systematic tool for upset recovery and prevention. But the widely used flight simulator is equipped with classic motion-sensing simulation algorithm, which is very intuitive, so only part workspace is used as the gain is fixed. However, during the state of non-normal flight, it is accompanied by abnormal aircraft attitude, angular velocity and acceleration substantial changes. The conservative motion-sensing simulation algorithm has limited capacity to simulate inertial motion of abnormal state, so integrated motion-sensing simulation algorithm is proposed to solve this problem.Firstly, the design process of motion-sensing simulation algorithm is analyzed in detail, and describe how to design high-pass filter and low pass filter, then use human vestibular system model to evaluate the performance of the filter with revised parameters. A complete method of filter design, evaluation and optimization is established.Secondly, switching control system is introduced to solve the conservative issues. Optimizing the algorithm for special flight state in first, the filter with excellent performance can take full use of platform movement ability, at the same time by monitoring controller to forecast the change of flight state, using soft switching method to switch the output of motion-sensing simulation algorithm.Two high pass filters are used in the algorithm, they move the platform back to the neutral position after a motion simulation was completed, so the neutral position become the home position for the next motion simulation. But because of the large range of motion in abnormal flight state, the neutral positon is not the best starting point, therefore, prepositioning is used to forecast the change of flight state, and calculate the best starting point.Finally, model of integrated motion-sensing simulation algorithm is established. Then use data to compare the performance of two kinds of algorithm. Simulation result show that the revised algorithm expand the use of platform capacity and improve the simulation fidelity.