Prespecified-time Synchronization of the Neural Networks via Smooth Controllers - SHAO Shao;WANG Xia;LIU Xiaoyang;HUANG Junwei (Nantong Daxue xuebao. Ziran kexue ban)
This paper considers the prespecified-time master-slave synchronization of the neural networks. Based on the regular state feedback and the time-varying gain function, this paper designs a new smooth control protocol to achieve the synchronization of the neural networks in a prespecified time. Different from the traditional finite-time or the fixed-time control, the synchronization time can be assigned in advance according to the task requirements, and thus it has the better practicability. Meanwhile, the synchronization time in the proposed protocol is independent of any initial values or controller parameters, which is essentially different from most existing finite-time control methods.Besides, the proposed protocol does not use the discontinuous or non-smooth state feedbacks, which reduces the difficulty in the theoretical analysis. Finally, some numerical simulations confirm the effectiveness of the theoretical analysis.