Synchronization for distributed parameter NNs with mixed delays via sampled-data control

Abstract

A sampled-data synchronization scheme is developed for a class of distributed parameter neural networks with mixed time delays. The design approach of the desired sampled data controller is also presented. We propose a sampled-data controller design, in which the sampled-data (in time) measurements of the state are taken in a finite number of fixed sampling points in the spatial domain. It is supposed that the sampling intervals in time and in space are bounded. Based on the extended Wirtinger’s inequality, an appropriate Lyapunov–Krasovskii functional and some free-weighting matrices are used to establish simple and less conservative synchronization criteria, which can ensure that the master systems synchronize with the slave systems via direct Lyapunov approach in terms of linear matrix inequalities. Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed synchronization method.