Hub moment limit protection using neural network prediction

A main rotor hub moment limit protection system is proposed and evaluated in a real-time piloted simulation. The system is designed to allow aggressive maneuvering while reducing the likelihood of "worst case" hub loads. The system has three major components: limit parameter response prediction, control margin calculation, and pilot cueing. A method for predicting the future response of transient limit parameters using measured aircraft states has been suggested. The algorithm uses non-linear time response functions that are represented with neural networks. Stick constraints were calculated using the predicted response and the peak value of the limit parameter to a unit step control input. The stick constraints were conveyed to the pilot using softstop cues. The system was evaluated in simulation and results showed that the prediction algorithms were effective. A formal handling qualities evaluation was not conducted, but pilot comments indicated some objectionable characteristics in the soft stop cueing. Further research on new methods of tactile cueing is warranted.