Adaptive synchronization of delayed reaction-diffusion FCNNs via learning control approach

A new adaptive learning control strategy is used to solve the synchronization problem for delayed reaction-diffusion fuzzy cellular neural networks with unknown periodically time-varying parameters. By constructing suitable Lyapunov-Krasovskii-like composite energy functional and employing some analysis techniques, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to achieve the adaptive synchronization of reaction-diffusion fuzzy cellular neural networks with unknown periodically time-varying parameters. Finally, a numerical example is presented to show the effectiveness of the proposed synchronization approach.

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