高速列车横向振动自适应神经模糊控制的仿真

为了设计出智能的列车悬挂系统,提出了基于神经网络的自适应模糊控制。模糊控制主要是针对系统的非线性;神经网络控制是产生模糊控制的控制规则。通过自适应神经网络的模糊推理系统(ANFIS),把神经网络和模糊控制相结合。神经网络根据采集的数据来进行训练,产生不同的控制规则,使模糊控制器对路面的变化具有自适应能力。仿真结果表明:该方法可在一定程度上减少轨道对列车车身的振动,提高列车在路面行驶的平稳性。

Study of Self-adaptive Neural Network Fuzzy Control for Transverse Vibration of High-speed Railway Vehicle

In order to design intelligent train suspension system,a kind of method based on neural network and adaptive fuzzy control is put forward.The fuzzy control is used to cope with the nonlinearity of the system.Neural network control is used to generate the fuzzy control rules.Through the adaptive neural fuzzy inference system(ANFIS),neural network and fuzzy control is combined,neural network collect and train data in order to produce different control rules.It makes the controller to be adapted to a variety of roads.The result shows that the method can be reduced the train body vibration,and hence improve the ride comfort of the vehicle to a higher extent.