Logistic人口增长模型的混沌数据系统及反馈控制研究

Primal chaos data system and feedback control research of Logistic population increase model

针对Logistic人口增长模型由稳定状态,通过控制参量的变化进入倍周期分岔及混沌,提出了一种基于Lyapunov指数的状态反馈控制策略,使混沌状态的Logistic模型变成为可测。该控制策略可将混沌状态的Logistic人口增长模型快速的收敛于给定的任意值,并进行了数字仿真。所有计算及作图由MathCad7.0实现。

A state feedback control strategy based on Lyapunov exponent is put forward, by change of control parameter into double periodicity fork and primal chaos. It makes Logistic model of primal chaos state measurable. The control strategy can make Logistic population increase model of primal chaos state fast converge to a given arbitrary value and given number simulation. All calculations and constructions are realized by MathCad7.0.