Practical fixed time active control scheme for synchronization of a class of chaotic neural systems with external disturbances. (April 2022) - Su, Haipeng; Luo, Runzi; Huang, Meichun; Fu, Jiaojiao
Highlights: The practical fixed-time synchronization for a class of chaotic neural networks in the presence of external disturbances is investigated. A novel practical fixed-time stability criterion, which can be viewed as the generalization of the existed result, is set up. An effective fixed time control approach to realize the practical synchronization of chaotic neural networks within a limited time is developed Different from traditional methodologies that dealt with the external disturbances, the chatter phenomenon can be avoided. Numerical example is presented to verify the effectiveness of the proposed schemes. Abstract: The objective in this work is to consider the practical fixed-time synchronization of delayed chaotic neural networks interfered by uncertain impacts. Firstly, to derive the sufficient conditions of fixed time stability, a novel practical fixed-time stability criterion, which can be viewed as the generalization of the existed results, is set up. Then, by means of the obtained stability criterion, we develop an effective fixed time control approach to attain the practical network synchronization within a limited time. In our synchronization scheme, the error state trajectories of two chaotic neural networks move forward to the small domain of zero in a short time freeing from the initial states. Besides, different from the traditional methodologies that dealt with the external disturbances, the chatter phenomenon can be avoided since our proposed controllers don't contain the signum functions. Finally, the effectiveness of the obtained theoretical results and synchronization scheme are testified by conducting the simulations.