混沌系统的RBF网络补偿控制方法研究

Studies on RBF networks compensative control of chaotic system

针对混沌系统由线性和非线性两部分构成的特点,提出径向基函数网络(RBFNs)补偿控制非线性混沌运动的方法,用训练好的RBF网络消除混沌系统非线性因素影响,将原系统变成近似线性系统,再利用设计好的线性状态反馈控制器将混沌系统镇定到希望平衡位置.在理论分析的基础上,通过典型的连续时间混沌系统(Holmes非线性振子)进行计算机仿真实验,结果表明,所提出方法具备有效性.图4,参12.

In view of the property of nonlinear chaotic systems composed of a sum of a linear and nonlinear part, a compensative control method using radial basis function networks (RBFNs) is presented, the trained RBF networks can eliminate the nonlinear part of the chaotic system, the resulting system is dominated by the linear part. Then, a designed linear statefeedback controller is used to suppress the system to a desirable position. In addition to theoretical analysis, the computer simulations on the representative continuoustime chaotic system (Holmes nonlinear oscillator) show the effectiveness of the proposed method.4figs.,12refs.