NEURO-FUZZY MODELING AND CONTROL

Fundamental and advanced developments in neuro-fuzzy synergisms for mo deling and control are reviewed. The essential part of neuro-fuzzy syn ergisms 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 Fu zzy Inference System (ANFIS), which possess certain advantages over ne ural networks. We introduce the design methods for ANFIS in both model ing and control applications. Current problems and future directions f or neuro-fuzzy approaches are also addressed.