The Study On Attack Helicopter Adaptive Flight Control System Using Neural Network

The design of neural-networks-based adaptive flight control system for helicopter is studied in this dissertation, which involving several aspects about inverse dynamics design for helicopter flight control system, compensating inverse error by wavelet neural-networks, maneuver flight simulation for helicopter.Because model of helicopter is a highly coupled unstable nonlinear system, a group of nonlinear motion equations are established firstly, and then analyzed the infection of the couple of motion and the couple of control of the free helicopter. This work supplied the physics concept for the design of the flight control system.In this dissertation the control loop of attitude angle is designed with dynamic inversion scheme. The controller is designed at two time scales. And the simulation shows the uncoupling of three attitude angle loop is achieved with dynamic inversion scheme.Adaptive wavelet neural network is introduced to compensate the inversion error resulted from inaccurate model of helicopter. The dissertation discussed wavelet theory and gave the formation of the wavelet function. In order to compensate the inversion error, the dissertation studied the BP based wavelet neural network firstly, and gave the learning rate; then studied the Lyapunov based wavelet neural network, and the adaptive control law of on-line neural network is discussed at great length. Two neural network controllers designed for both methods. The simulations show the both controller could compensate inversion error effectively.Finally, the dissertation designed the fuzzy PD controller of trajectory tracking, which is combined with attitude angle controller, so that the whole flight controller is completed. The simulation of two typical maneuver (BopUp-BopDown and S maneuver flight) shows that the maneuverable of attack helicopter is improved by the control system.