摘要
将一种神经—模糊结构—自适应神经模糊推理系统 (简称ANFIS)用于非线性电机系统的建模 ,获得了一个良好的大范围的全局非线性模型 ,同时 ,通过与反向传播网络建模结果的性能对比 ,说明ANFIS在参数收敛速度及建模精度上的优越性。显示出ANFIS是非线性系统的建模。
A neural fuzzy construction adaptive neural fuzzy inference system (ANFIS) is used to model nonlinear electric motor system in this paper. A good global nonlinear model in a large scale is obtained, and at the same time, the advantages in the convergence velocity and in the accuracy of the modeling are illustrated by means of the comparison with the property of back propagation network, which shows that the ANFIS is a powerful tool of modeling and discriminating the nonlinear system.
出处
《基础自动化》
CSCD
2002年第1期6-8,共3页
Basic Automation
关键词
非线性电机系统
建模
ANFIS
混合学习算法
隶尿函数
nonlinear dynamic system
neural fuzzy modeling
adaptive neural fuzzy inference system (ANFIS)
back propagation neural networks(BPNN)
hybrid learning algorithm
