Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer
研究了扑翼微型飞行器的姿态与位置控制，设计了带扰动观测器的神经网络控制器以应对系统不确定性和扰动，仿真表明能良好跟踪轨迹。
The research of this paper works out the attitude and position control of the flapping wing micro aerial vehicle (FWMAV). Neural network control with full state and output feedback are designed to deal with uncertainties in this complex nonlinear FWMAV dynamic system and enhance the system robustness. Meanwhile, we design disturbance observers which are exerted into the FWMAV system via feedforward loops to counteract the bad influence of disturbances. Then, a Lyapunov function is proposed to prove the closed-loop system stability and the semi-global uniform ultimate boundedness of all state variables. Finally, a series of simulation results indicate that proposed controllers can track desired trajectories well via selecting appropriate control gains. And the designed controllers possess potential applications in FWMAVs.