Affine Memory Control for Synchronization of Delayed Fuzzy Neural Networks

This paper deals with the synchronization of fuzzy neural networks (FNNs) with time-varying delays. FNNs are more complicated form of neural networks incorporated with fuzzy logics, which provide more powerful performances. Especially, the problem of delayed FNNs's synchronization is of importance in the existence of the network communication. For the synchronization of FNNs with time-varying delays, a novel form of control structure is proposed employing affinely transformed membership functions with memory element. In accordance with affine memory control, appropriate Lyapunov-Krasovskii functional is chosen to design control gain, guaranteeing stability of the systems with delays. Exploiting the more general type of control attributed by affine transformation and memory-type, a novel criterion is derived in forms of linear matrix inequalities (LMIs). As a results, the effectiveness of the proposed control is shown through numerical examples by comparisons with others.