Adaptive Neural Network Control of Small Unmanned Aerial Rotorcraft

作者：Lei Xusheng^*; Ge Shuzhi Sam; Fang Jiancheng

来源：Journal of Intelligent & Robotic Systems, 2014, 75(2): 331-341.

DOI：10.1007/s10846-013-0017-2

• Small unmanned aerial rotorcraft
• Adaptive neural network
• Feedback control
• Disturbances

This paper proposes an online learning adaptive neural network for small unmanned aerial rotorcraft to improve control performance during flight. Based on state error information, the weight matrix of the adaptive neural network can be updated on line by using lyapunov function. Therefore, no prior training data is needed for the training of the adaptive neural network. Combined with feedback control, the adaptive neural network can construct the map between the state error information and disturbances to compensate for system disturbances. The effectiveness of the proposed method is validated by a series of simulations and flight tests. Compared with feedback control method, the adaptive neural network control method can estimate and eliminate disturbances quickly to yield a good tracking performance.

• 出版日期2014-8
• 单位北京航空航天大学