Using Genetic-Fuzzy-Neuro Model to Design Dual-FNNs Controller
Kaijun Xu, Jiajun Lai, Shuiting Wu, Xu Yang · 2007
During the last decade, there has been increased use of neural networks (NNs), fuzzy logic (FL) and genetic algorithms (GAs) in artificial intelligence (AI).Since these three methods are complementary rather than competitive, a better performance model which has combined GAs, FL and NNs comes into being gradually.This paper presents genetic-fuzzy-neuro (G-F-N) model to design the dual-fuzzy neural-networks (DFNNs) controller.For the convenience of adaptive control, the structure of the two-fuzzy neural-network controller is divided into two parts.Each part is a fuzzy neural-network (FNN).The adaptive controller uses two FNNs.One FNN is used to identify a fuzzy model of controlled object.The other is onlinetracking learning the suitable control policy.