Exponential stabilization for fractional intermittent controlled multi-group models with dispersal

Abstract Multi-group models have attracted considerable attention due to their promising potential applications in various fields. In this paper, aperiodically intermittent control is designed to study the exponential stability of fractional-order multi-group models with dispersal. By applying Lyapunov method and graph theory, some sufficient conditions about exponential stability are established. From the theoretical results, we observe that the convergence speed depends on the control gain and the order of fractional derivative. Moreover, to show the practicality of theoretical results, we provide an application of modified fractional-order competitive neural networks. A stability criterion is also given to guarantee the exponential stability of modified fractional-order competitive neural networks. Finally, a numerical example is provided to show the effectiveness of the stated results. Some simulation comparisons are also carried out to illustrate the relationship between the convergence speed and the control gain with the order of fractional derivative.

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