永磁同步电机的模糊混沌神经网络建模

Fuzzy Chaos Neural Network Modeling of Permanent Magnet Synchronous Motor

采用模糊混沌神经网络建立了具有混沌特性的永磁同步电机(PMSM)模型。永磁同步电机在一定工作情况下呈现混沌运动,根据PMSM的数学模型得出其混沌特性曲线。将混沌神经网络与模糊理论相结合设计出协作型模糊混沌神经网络,并据此网络建立了永磁同步电机的模糊混沌神经网络结构模型,该模型在结构上为神经网络,具有混沌特性,在功能上是模糊系统；确定了模型的输出函数,并推导了模型的学习算法,仿真结果表明永磁同步电机的模糊混沌神经网络模型与原系统是等价的。

Permanent magnet synchronous motors （PMSM） model with chaotic features was built based on fuzzy chaos neural network. PMSM showed chaotic movement under certain circumstances. Trajectory curves were gained based on PMSM mathematic model. Combined chaos neural network with fuzzy theory, designed coordinated fuzzy chaos neural network, built PMSM＇s fuzzy chaos neural network model based on the network. The model was structurally neural network with chaotic features and functionally fuzzy system. It established the model＇s output mathematic function and learning algorithm. Computer simulations showed the equivalence of fuzzy chaos neural network model and the original chaotic system.