摘要
针对分数阶混沌系统的控制问题,提出了一种基于径向基函数(RBF)神经网络的控制方法.利用RBF神经网络对混沌系统的非线性进行补偿,并且神经网络的权值可以通过调整律在线调整.在有参数干扰和外部扰动的情况下,所设计的控制器仍能使得控制误差渐近收敛到零.以分数阶Liu混沌系统为例施加控制,仿真结果验证了该方法的有效性和鲁棒性.
For the control of fractional order chaotic systems, a new method based on RBF （radial basis function） neural network is presented. RBF neural network is designed for the nonlinear compensation in chaotic systems, and the weights of RBF neural network can be adjusted on-line via the update law. The proposed controller can make the control error converge to zero asymptotically, even with parametric perturbation and external disturbances. Chaos control for fractional order Liu system is implemented as an example. The simulation results prove the effectiveness and the robustness of the proposed method.
出处
《信息与控制》
CSCD
北大核心
2010年第2期142-146,共5页
Information and Control
关键词
分数阶
混沌控制
RBF神经网络
fractional order
chaos control
RBF neural network
