Adaptive control of neural network systems containing time-varying delay

In this paper, we handle the problem of adaptive control of neural network systems subjected to time-varying delay. First of all, a simple adaptive control strategy is designed by combining adaptive scheme and linear feedback with the updated feedback strength, which is strictly proved in the framework of Krasovskii-Lyapunov theory and is valid for generic high-dimensional nonlinear systems containing constant or time-varying delay. By the proposed method, the controlled orbit of a Hopfield neural network system containing time-varying delay can track the target orbit quickly, which verifies the effectiveness of the proposed method.