Adaptive control-based synchronization of discrete-time fractional-order fuzzy neural networks with time-varying delays

Hong-Li Li; Jinde Cao; Cheng Hu; Long Zhang; Haijun Jiang

doi:10.1016/j.neunet.2023.09.019

Adaptive control-based synchronization of discrete-time fractional-order fuzzy neural networks with time-varying delays

Neural Netw. 2023 Nov:168:59-73. doi: 10.1016/j.neunet.2023.09.019. Epub 2023 Sep 19.

Authors

Hong-Li Li¹, Jinde Cao², Cheng Hu³, Long Zhang³, Haijun Jiang⁴

Affiliations

¹ College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China; School of Mathematics, Southeast University, Nanjing 210096, China. Electronic address: lihongli@xju.edu.cn.
² School of Mathematics, Southeast University, Nanjing 210096, China; Yonsei Frontier Lab, Yonsei University, Seoul 03722, South Korea. Electronic address: jdcao@seu.edu.cn.
³ College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China.
⁴ College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China; School of Mathematics and Statistics, Yili Normal University, Yining 835000, China.

PMID: 37742532
DOI: 10.1016/j.neunet.2023.09.019

Abstract

This paper is concerned with complete synchronization for discrete-time fractional-order fuzzy neural networks (DFFNNs) with time-varying delays. First, three original equalities and two Caputo σ-difference inequalities are established based on theory of discrete-time fractional Calculus. Next, a novel discrete-time adaptive controller with time-varying delay is designed, by virtue of 1-norm Lyapunov function and newly established lemmas herein as well as inequality techniques and contradiction method, some judgement conditions are derived to guarantee complete synchronization for the explored DFFNNs. Benefitting from discrete-time adaptive control strategy and our analysis method, the conservatism of the derived synchronization criteria is reduced. Ultimately, the effectiveness of our theoretical results and secure communication scheme are demonstrated through two numerical examples.

Keywords: Adaptive control; Complete synchronization; Discrete-time fractional-order; Fuzzy neural networks; Time-varying delays.

MeSH terms

Algorithms*
Communication
Neural Networks, Computer*
Time