Adaptive Synchronization of Coupled Chaotic Delayed Systems Based on Parameter Identification and Its Applications

This paper investigates synchronization dynamics of a large class of chaotic delayed systems with all the parameters unknown. By a simple combination of adaptive control and linear feedback with the updated laws, some simple yet generic criteria for determining global synchronization based on parameter identification of uncertain chaotic delayed systems are derived by using the invariance principle of functional differential equations. It is shown that the approaches developed here further extend the ideas and techniques presented in recent literature. Furthermore, the theoretical results are applied to the well-known Chua's circuit and a typical class of chaotic delayed Hopfied neural networks, and numerical simulations also demonstrate the effectiveness and feasibility of the proposed techniques.