基于神经网络的机翼振动主动控制

根据DARMA模型提出了简单易用的神经网络控制方案，该方法采用线性人工神经网络对系统动态特性进行在线辨识，并利用辨识得到的信息，采用BP神经网络对系统进行控制，将该算法应用于飞机机翼振动主动控制数值仿真。仿真结果表明，该方法能减少算法的计算量，压缩计算时间，便于提高系统采样频率，使得自由振动和调频振动的抑制成为可能。

Active Control of Airfoil Vibration Based on Neural Network

A new neural network adaptive control method is proposed based on the DARMA model. In this method, a linear neural network identifies on-line dynamic characteristics of the control system, and the information by identification is adopted to control system by Back-Propagation neural networks. The method is implemented in the simulation of active control for airfoil vibration. The results of the simulation indicate that the method can reduce the workload of algorithm,compress the time of calculate and improve the system sampling frequency. It makes possibility of controlling freedom vibration and frequency modulation vibration.