参数微扰激光超混沌系统模糊模型

研究了存在参数微扰的激光超混沌系统的Takagi-Sugeno (T-S) 模糊模型的逼近性及建立问题。分析了存在参数微扰的激光超混沌系统的动力学特性。基于典型T-S模糊系统的建模原理,研究了激光超混沌T-S模糊系统的通用逼近性,通过确定非线性关键变量、模糊隶属度函数及模糊规则,建立了激光超混沌系统的T-S模糊模型。仿真结果表明,所建立的模糊模型能够有效逼近存在参数微扰的激光超混沌系统。     

Synchronization Scheme for Uncertain Chaotic Systems via RBF Neural Network

A sliding mode adaptive synchronization controller is presented with a neural network of radial basis function （RBF） for two chaotic systems. The uncertainty of the synchronization error system is approximated by the RBF neural network. The synchronization controller is given based on the output of the RBF neural network. The proposed controller can make the synchronization error convergent to zero in 5s and can overcome disruption of the uncertainty of the system and the exterior disturbance. Finally, an example is given to illustrate the effectiveness of the proposed synchronization control method.