期刊
FRACTAL AND FRACTIONAL
卷 7, 期 4, 页码 -出版社
MDPI
DOI: 10.3390/fractalfract7040288
关键词
radial basis neural network; Lyapunov stability theory; fractional-order time-delay chaotic system
We propose an adaptive radial basis neural network controller based on Lyapunov stability theory for uncertain fractional-order time-delay chaotic systems with different time delays. The controller achieves synchronous control without knowledge of the system model and in the presence of unknown nonlinear uncertainties and external disturbances. Stability analysis demonstrates that the error system asymptotically tends to zero in combination with a relevant lemma. Numerical simulations confirm the effectiveness of the controller.
We propose an adaptive radial basis (RBF) neural network controller based on Lyapunov stability theory for uncertain fractional-order time-delay chaotic systems (FOTDCSs) with different time delays. The controller does not depend on the system model and can achieve synchronous control under the condition that nonlinear uncertainties and external disturbances are completely unknown. Stability analysis showed that the error system asymptotically tended to zero in combination with the relevant lemma. Numerical simulation results show the effectiveness of the controller.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据