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Impulsive control for persistence and periodicity of logistic systems

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  • Sun, Li
  • Zhu, Haitao
  • Ding, Yanhui

Abstract

In this paper, a class of logistic systems with impulsive effects are proposed and investigated. Based on impulsive control theory, a novel approach is developed to guarantee the persistence and existence of a unique globally attractive positive periodic solution. The development results of this paper emphasize the impulsive effects on system, which are different from the existing ones in the literature. Two examples and their simulations are given to illustrate the effectiveness of the proposed results.

Suggested Citation

  • Sun, Li & Zhu, Haitao & Ding, Yanhui, 2020. "Impulsive control for persistence and periodicity of logistic systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 294-305.
    • Handle: RePEc:eee:matcom:v:171:y:2020:i:c:p:294-305
    DOI: 10.1016/j.matcom.2019.06.006
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    References listed on IDEAS

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    1. Nie, Rencan & Cao, Jinde & Zhou, Dongming & Qian, Wenhua, 2019. "Analysis of pulse period for passive neuron in pulse coupled neural network," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 277-289.
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    4. Xinsong Yang & Chuangxia Huang & Zhichun Yang, 2012. "Stochastic Synchronization of Reaction-Diffusion Neural Networks under General Impulsive Controller with Mixed Delays," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-25, December.
    5. Li, Zhong & Han, Maoan & Chen, Fengde, 2014. "Almost periodic solutions of a discrete almost periodic logistic equation with delay," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 743-751.
    6. Shi, Yanchao & Cao, Jinde & Chen, Guanrong, 2017. "Exponential stability of complex-valued memristor-based neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 313(C), pages 222-234.
    7. Chen, Xiaofeng & Zhao, Zhenjiang & Song, Qiankun & Hu, Jin, 2017. "Multistability of complex-valued neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 18-35.
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    Cited by:

    1. Cortés, J.-C. & Moscardó-García, A. & Villanueva, R.-J., 2022. "Uncertainty quantification for hybrid random logistic models with harvesting via density functions," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).

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