4.7 Article

Exponential Stability of Fractional-Order Complex Multi-Links Networks With Aperiodically Intermittent Control

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2020.3016672

Keywords

Control theory; Stability analysis; Numerical stability; Asymptotic stability; Biological neural networks; Aperiodically intermittent control; competitive neural networks; exponential stability; fractional-order complex networks; multiple links

Funding

  1. Shandong Province Natural Science Foundation [ZR2018MA005, ZR2018MA020, ZR2017MA008]
  2. Key Project of Science and Technology of Weihai [2014DXGJMS08]
  3. Innovation Technology Funding Project in Harbin Institute of Technology [HIT.NSRIF.201703]

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This article examines the exponential stability problem of fractional-order complex multi-links networks under aperiodically intermittent control, and provides the theoretical results on how control gain and fractional derivative order affect the exponential convergence rate. The practicality of the theoretical results is demonstrated through investigating the stability of fractional-order competitive neural networks with aperiodically intermittent control and establishing a stability criterion, which is further validated through a numerical example.
In this article, the exponential stability problem for fractional-order complex multi-links networks with aperiodically intermittent control is considered. Using the graph theory and Lyapunov method, two theorems, including a Lyapunov-type theorem and a coefficient-type theorem, are given to ensure the exponential stability of the underlying networks. The theoretical results show that the exponential convergence rate is dependent on the control gain and the order of fractional derivative. To be specific, the larger control gain, the higher the exponential convergence rate. Meanwhile, when aperiodically intermittent control degenerates into periodically intermittent control, a corollary is also provided to ensure the exponential stability of the underlying networks. Furthermore, to show the practicality of theoretical results, as an application, the exponential stability of fractional-order multi-links competitive neural networks with aperiodically intermittent control is investigated and a stability criterion is established. Finally, the effectiveness and feasibility of the theoretical results are demonstrated through a numerical example.

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