Journal
IEEE ACCESS
Volume 6, Issue -, Pages 74240-74246Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2883417
Keywords
Neural network; synchronization; fixed-time control; the convergence time
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Funding
- National Natural Science Foundation of China [61673221, 61573262]
- Natural Science Foundation of Jiangsu Province [BK20181418]
- Qing-Lan Engineering'' Foundation of Jiangsu Higher Education Institutions
- Six Talent Peaks Project in Jiangsu Province [DZXX-019]
- Natural Science Fund for Distinguished Young Scholars of Hubei Province [2017CFA052]
- Applied Economics of Nanjing Audit University of the Priority Academic Program Development of Jiangsu Higher Education Institutions (Office of Jiangsu Provincial People's Government) [[2018]87]
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This paper discusses synchronization of time-varying delayed neural networks by fixed-time control. First, several new fixed-time stability theorems of the dynamic system are discussed, and the estimation of the convergence time is also gained. Compared with some existing results, the convergence time given in this paper can be less conservative and more accurate. Second, as one of the important applications of fixed-time stability, several novel sufficient criteria are derived such that the two time-varying neural networks can be synchronized within a fixed-time. Finally, the simulation result is presented to show the effectiveness of the theoretical result.
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