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Bifurcations and chaos control in a discrete-time biological model
International Journal of Biomathematics ( IF 2.2 ) Pub Date : 2020-01-31 , DOI: 10.1142/s1793524520500229
A. Q. Khan 1 , T. Khalique 1
Affiliation  

In this paper, bifurcations and chaos control in a discrete-time Lotka–Volterra predator–prey model have been studied in quadrant-[Formula: see text]. It is shown that for all parametric values, model has boundary equilibria: [Formula: see text], and the unique positive equilibrium point: [Formula: see text] if [Formula: see text]. By Linearization method, we explored the local dynamics along with different topological classifications about equilibria. We also explored the boundedness of positive solution, global dynamics, and existence of prime-period and periodic points of the model. It is explored that flip bifurcation occurs about boundary equilibria: [Formula: see text], and also there exists a flip bifurcation when parameters of the discrete-time model vary in a small neighborhood of [Formula: see text]. Further, it is also explored that about [Formula: see text] the model undergoes a N–S bifurcation, and meanwhile a stable close invariant curves appears. From the perspective of biology, these curves imply that between predator and prey populations, there exist periodic or quasi-periodic oscillations. Some simulations are presented to illustrate not only main results but also reveals the complex dynamics such as the orbits of period-2,3,13,15,17 and 23. The Maximum Lyapunov exponents as well as fractal dimension are computed numerically to justify the chaotic behaviors in the model. Finally, feedback control method is applied to stabilize chaos existing in the model.

中文翻译:

离散时间生物模型中的分岔和混沌控制

在本文中,离散时间 Lotka-Volterra 捕食者-猎物模型中的分岔和混沌控制已在象限-[公式:见正文]中进行了研究。结果表明,对于所有参数值,模型具有边界平衡:[公式:见文本],以及唯一的正平衡点:[公式:见文本] if [公式:见文本]。通过线性化方法,我们探索了局部动力学以及关于平衡的不同拓扑分类。我们还探讨了正解的有界性、全局动力学以及模型的主要周期和周期点的存在性。探讨了在边界均衡发生翻转分岔:[公式:见正文],并且当离散时间模型的参数在[公式:见正文]的一个小邻域内变化时,也存在翻转分岔。进一步,还探讨了[公式:见正文]模型经历了N-S分岔,同时出现了稳定的闭合不变量曲线。从生物学的角度来看,这些曲线暗示捕食者和猎物种群之间存在周期性或准周期性振荡。一些模拟不仅说明了主要结果,而且揭示了复杂的动力学,例如周期 2、3、13、15、17 和 23 的轨道。最大 Lyapunov 指数和分形维数被数值计算以证明模型中的混沌行为。最后,采用反馈控制方法来稳定模型中存在的混沌。这些曲线表明捕食者和猎物种群之间存在周期性或准周期性振荡。一些模拟不仅说明了主要结果,而且揭示了复杂的动力学,例如周期 2、3、13、15、17 和 23 的轨道。最大 Lyapunov 指数和分形维数被数值计算以证明模型中的混沌行为。最后,采用反馈控制方法来稳定模型中存在的混沌。这些曲线表明捕食者和猎物种群之间存在周期性或准周期性振荡。一些模拟不仅说明了主要结果,而且揭示了复杂的动力学,例如周期 2、3、13、15、17 和 23 的轨道。最大 Lyapunov 指数和分形维数被数值计算以证明模型中的混沌行为。最后,采用反馈控制方法来稳定模型中存在的混沌。
更新日期:2020-01-31
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