Optimized neural network-direct inverse control for attitude control of heavy-lift hexacopter

This paper discusses a neural network based on direct inverse control (DIC) to control the roll, pitch, and yaw in maintaining the hovering condition of a heavy-lift hexacopter. To improve the control of the hexacopter, the authors propose a DIC-optimized method of retraining the inverse model using new data collected from optimal motions of the hexacopter generated by the desired input. The experiment showed that both the DIC model and the DIC-optimized model had good performances with small MSSE valueshowever, the latter was more effective than the former