基于压缩传感的混沌自适应控制

提出了一种自适应混沌控制方法,仅根据输出时间序列,利用压缩传感辨识混沌系统的方程与参数,利用负反馈控制混沌系统到设定目标上。以Lorenz和Rssler系统为例说明时变结构系统的方程及参数的辨识与控制,首先估计出Lorenz系统方程并将其控制到固定点或周期振荡上,当系统结构从Lorenz变化到Rssler时可以快速辨识新结构及其参数,系统重新回到控制目标上。结果表明,与最小二乘法相比,该方法仅通过较少的数据即可实现模型结构与参数的同时估计,并有很高的估计精度,利用估计得到的模型和参数,再利用负反馈可以将混沌系统快速控制到设定目标上。

Adaptive control of chaos based on compressive sensing

An adaptive chaos control method is proposed,using compressed sensing to identify equations and parameters of chaotic systems based only on the output time series,and using negative feedback control of chaotic system to set goals.Lorenz and the Rssler system is used to illustrate the identfication and control of equations and parameters of the time-varying structure system.First the Lorenz system is controlled to a fixed point or periodic oscillations.When the structure changes to Rssler,the new structure and its parameters is recognized,and the system retruns to the control objectives again.The results show that,compared to least-squares method,the method can be realized with less data,while the model structure and parameters are estimated with high accuracy.Then negative feedback can be used to control rapidly the system to the set goals.