Modeling and Adaptive Control with Fuzzy Neural Networks - Selected Papers from the 6th International Symposium on Neural Networks

Both neural networks and fuzzy logic systems are universal estimators. Recent results show that the fusion procedure of these two different technologies has significant advantages over standard feedback controllers for unknown nonlinear systems. The purpose of this special issue is to bring together fuzzy neural networks and adaptive control design techniques. This special issue of Neurocomputing presents seven original articles, which are extended versions of selected papers from the 6th International Symposium on Neural Networks (ISNN 2009), May 26–29, 2009, Wuhan, China. The contributions of this issue reflect the well-known fact that ISNN traditionally covers a broad variety of the thoroughness of techniques deployed for new analysis and learning methods of neural networks. Based on the recommendation of the special session organizers and the reviews of the conference papers, a number of authors were invited to submit an extended version of their conference paper for this special issue of Neurocomputing. All the invited articles were thoroughly reviewed once more by at least two independent experts and, finally, the seven articles presented in this volume were accepted for publication.