Adaptive Semi-Periodically Intermittent and Lag Synchronization Control of Neural Networks With Mixed Delays

Abstract

In this paper, the lag exponential synchronization for a class of neural networks with distributed delays and discrete delays (mixed delays) is studied via adaptive semiperiodically intermittent control. Using the adaptive control theory, the Lyapunov stability theory combined with the method of intermittent control, the simple but robust adaptive semiperiodically intermittent controller and impulse controller are designed. Via the proposed control methods, the response system can lag synchronize with the drive system, and the less conservative results are obtained. Using the adaptive control approach and giving a rigorous proof for the synchronization scheme, the proposed controllers are obviously little costly and more useful in practice than before. In the original references, the control width should be larger than the time delay and the time delay should be smaller than the noncontrol width. While, in this paper, these strict assumptions can be removed. Moreover, the control time and the control rate may not be constants. This leads to a larger application scope for our method. Last, numerical simulations are exploited to show the effectiveness of the results.

Keywords

• Neural networks
• mixed delays
• lag synchronization
• adaptive control
• semi-periodically intermittent control