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Hybrid tactics for bifurcation control in a fractional-order delayed predator–prey model

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  • Zhou, Weigang
  • Huang, Chengdai
  • Xiao, Min
  • Cao, Jinde

Abstract

This paper handles the problem of controlling bifurcation for a fractional delayed predator–prey system via active hybrid control strategy. Delay-induced bifurcation conditions of the Hopf bifurcation are achieved for controlled model by using time delay as a bifurcation parameter. It is illustrated that the stability performance is drastically enhanced with the help of the proposed controller, yet Hopf bifurcation emerges in advance if the controller is removed. Finally, numerical simulations are carried out to confirm our theoretical analysis.

Suggested Citation

  • Zhou, Weigang & Huang, Chengdai & Xiao, Min & Cao, Jinde, 2019. "Hybrid tactics for bifurcation control in a fractional-order delayed predator–prey model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 183-191.
  • Handle: RePEc:eee:phsmap:v:515:y:2019:i:c:p:183-191
    DOI: 10.1016/j.physa.2018.09.185
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    References listed on IDEAS

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    1. Huang, Chengdai & Cao, Jinde & Xiao, Min & Alsaedi, Ahmed & Hayat, Tasawar, 2017. "Bifurcations in a delayed fractional complex-valued neural network," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 210-227.
    2. Abernethy, Gavin M. & Mullan, Rory & Glass, David H. & McCartney, Mark, 2017. "A multiple phenotype predator–prey model with mutation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 762-774.
    3. Huang, Chengdai & Cao, Jinde & Xiao, Min & Alsaedi, Ahmed & Alsaadi, Fuad E., 2017. "Controlling bifurcation in a delayed fractional predator–prey system with incommensurate orders," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 293-310.
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    5. Camara, B.I. & Haque, M. & Mokrani, H., 2016. "Patterns formations in a diffusive ratio-dependent predator–prey model of interacting populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 374-383.
    6. Wang, Fei & Yang, Yongqing, 2018. "Quasi-synchronization for fractional-order delayed dynamical networks with heterogeneous nodes," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 1-14.
    7. Li, Li & Wang, Zhen & Li, Yuxia & Shen, Hao & Lu, Junwei, 2018. "Hopf bifurcation analysis of a complex-valued neural network model with discrete and distributed delays," Applied Mathematics and Computation, Elsevier, vol. 330(C), pages 152-169.
    8. Wang, Xuedi & Peng, Miao & Liu, Xiuyu, 2015. "Stability and Hopf bifurcation analysis of a ratio-dependent predator–prey model with two time delays and Holling type III functional response," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 496-508.
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    Cited by:

    1. He, Haoming & Xiao, Min & Lu, Yunxiang & Wang, Zhen & Tao, Binbin, 2023. "Control of tipping in a small-world network model via a novel dynamic delayed feedback scheme," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Du, Wentong & Xiao, Min & Ding, Jie & Yao, Yi & Wang, Zhengxin & Yang, Xinsong, 2023. "Fractional-order PD control at Hopf bifurcation in a delayed predator–prey system with trans-species infectious diseases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 414-438.
    3. Rihan, F.A. & Rajivganthi, C, 2020. "Dynamics of fractional-order delay differential model of prey-predator system with Holling-type III and infection among predators," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    4. Sekerci, Yadigar, 2020. "Climate change effects on fractional order prey-predator model," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).

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