工程车辆挡位决策的自适应神经模糊推理系统

Adaptive Neuro-fuzzy Inference System of Engineering Vehicle Shift Decision

提出了一种自适应神经模糊推理系统 ,并利用在 ZL 5 0 E装载机传动系统换挡实验中获得的数据进行验证性仿真。仿真结果表明 ,该挡位决策系统可根据操作工况环境实现正确的变速箱挡位决策。它将模糊推理与神经网络有机地结合起来 ,克服了模糊推理不具备学习功能和神经网络不能表达模糊语言的缺点 ,使模糊推理与神经网络的应用范围更加广泛 。

In order to improve the intelligence of engineering vehicle shift decision a kind of adaptive neuro fuzzy inference system (ANFIS) is proposed and a test simulation is developed based on the data obtained in shift experiment on ZL50E loader transmission system. The simulation results show that this shift decision system can realize correct gear box shift decision according to operation conditions. ANFIS combines fuzzy inference and neural network organically, overcoming the shortcomings that fuzzy inference doesn't have learning function and neural network can't express fuzzy language, making the application region of fuzzy inference and neural network wider, so this system is an effective method to realize shift decision.