基于神经网络和滑模控制的不确定混沌系统同步

基于滑模控制技术和径向基函数神经网络,设计出一种神经滑模控制器,实现了两个不确定混沌系统的同步.控制器的设计不依赖于系统的数学模型,只与系统的输出状态有关,而且对参数不确定性和外界干扰具有较强的稳健性.最后,利用本方法设计出控制器实现了未知Lorenz系统的自同步、未知Lorenz系统与Chen系统之间的异结构同步,而且响应时间短,同步效果好. 关键词： 混沌同步 滑模控制 神经网络 不确定混沌系统

Synchronization of uncertain chaotic systems based on neural network and sliding mode control

The synchronization between two unknown chaotic systems is achieved by designing a controller based on the sliding mode control technique and radial basis function neural network. The controller design method is independent of the system mathematical model, but only depends on the output of the system state. Moreover, it is robust to parameter uncertainties and the outside interference. Finally, synchronization between unknown Lorenz systems and between unknown Lorenz system and Chen system are achieved using the proposed method. The response time is very short and the synchronization performance is good.