Title :
Neuro-fuzzy modeling and control
Author :
Jang, Jyh-Shing Roger ; Sun, Chuen-Tsai
Author_Institution :
The MathWorks Inc., Natick, MA, USA
fDate :
3/1/1995 12:00:00 AM
Abstract :
Fundamental and advanced developments in neuro-fuzzy synergisms for modeling and control are reviewed. The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks is called adaptive-network-based fuzzy inference system (ANFIS), which possess certain advantages over neural networks. We introduce the design methods for ANFIS in both modeling and control applications. Current problems and future directions for neuro-fuzzy approaches are also addressed
Keywords :
adaptive systems; fuzzy control; fuzzy neural nets; inference mechanisms; neurocontrollers; adaptive networks; control applications; fuzzy inference system; fuzzy models; neural networks; neuro-fuzzy modeling; Adaptive systems; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Neural networks; Sun;
Journal_Title :
Proceedings of the IEEE