基于向量目标定向控制的结构种群镇定
Stabilization of structured populations via vector target oriented control
摘要：
与非结构化模型相比，结构化离散种群模型已经能够拟合和预测混沌实验数据。然而，在文献中的大多数混沌控制技术的设计和分析，在一维设置。在这里，通过引入离散动力系统的目标定向控制，我们证明了稳定一个选定的状态的广泛的结构人口模型的可能性。结果表明，在著名的LPA模型描述面粉甲虫动力学引入控制。此外，我们表明，新的控制允许稳定的周期解高阶差分方程，如延迟Ricker模型，以前的目标导向的方法没有设计。
英文摘要：
In contrast with unstructured models, structured discrete population models have been able to fit and predict chaotic experimental data. However, most of the chaos control techniques in the literature have been designed and analyzed in a one-dimensional setting. Here, by introducing target oriented control for discrete dynamical systems, we prove the possibility to stabilize a chosen state for a wide range of structured population models. The results are illustrated with introducing a control in the celebrated LPA model describing a flour beetle dynamics. Moreover, we show that the new control allows to stabilize periodic solutions for higher order difference equations, such as the delayed Ricker model, for which previous target oriented methods were not designed.
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