Study on disturbance attenuation of cellular neural networks with time-varying delays

Abstract The paper is concerned with the problem of disturbance attenuating controller design for delayed cellular neural networks (DCNNs). Via combining four different states cases in DCNNs and applying Razumikhin function analysis, a feedback control law in the form of linear matrix inequality (LMI) is derived for guaranteeing disturbance attenuation of the closed systems. Finally, a numerical example of DCNNs is given to indicate the effectiveness of the proposed disturbance attenuating control. Because there is no restriction that the time derivative of the delay is smaller than 1 which is a hypothesis of many articles concerning time-varying delayed systems, the proposed scheme has significance impact on the design and applications of the disturbance attenuating control. Meanwhile an example of CNNs is offered to show the usefulness of the controller to the systems without time delay.

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