基于神经网络的多柔性梁耦合结构振动控制

Vibration Control of Multiple Flexible Beams Coupling Structure Based on Neural Network

  • 摘要: 针对一种多柔性梁耦合结构进行研究,搭建了多柔性梁耦合结构实验平台,采用激光位移传感器对残余振动信号进行测量,并建立了有限元模型.为抑制其产生的残余振动,借助了神经网络的拟合效果,设计了神经网络控制器,包括了预测网络与控制网络.预测网络为长短时记忆(LSTM)神经网络,控制网络为反向传播(BP)网络,网络经过离线训练,并在线使用反向传播进行权值更新.通过仿真与实验,表明LSTM网络具有很好的预测作用,验证了神经网络控制器的有效性,总体上能更快抑制振动.

     

    Abstract: A multiple flexible beams coupling structure is investigated in this study, and an experimental platform of multiple flexible beams coupling structure is built. The laser displacement sensor is used to measure the residual vibration signal, and the finite element model is established. A neural network controller is designed to suppress the residual vibration, including prediction and control networks. The prediction network is long short-term memory (LSTM) neural network, and the control network is a backpropagation neural network. After off-line training, the network uses backpropagation to update the weights. The simulation and experimental results show that the LSTM network has a better predictive performance, which confirms the effectiveness of the neural network controller. In addition, it can suppress vibration faster.

     

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