Robust control system design by use of neural networks and its application to UAV flight control

Stochastic uncertainty are the most typical in flight control system, because wind direction and wind speed, which have significant effect on the flight, vary stochastically. We propose methods to design robust control systems by training a neural network against stochastic uncertainties. Numerical simulations of flight control of an autonomous unmanned helicopter demonstrate the effectiveness of proposed methods.