基于反演自适应动态滑模的FitzHugh-Nagumo神经元混沌同步控制

本文采用反演自适应动态滑模控制实现耦合FitzHugh-Nagumo (FHN) 神经元混沌同步. 该方法将自适应技术与反演控制方法相结合, 通过设计新型切换函数, 采用动态滑模控制律, 实现了带有不确定参数的耦合FHN神经元混沌放电同步. 研究表明该方法可以有效地削弱系统的抖振, 从而避免破坏神经元的本质特性, 且响应速度快. 仿真结果证明了该控制方法的有效性. 关键词： 自适应 动态滑模控制 FitzHugh-Nagumo神经元 混沌同步

Chaos synchronization of FitzHugh-Nagumo neurons via backstepping and adaptive dynamical sliding mode control

In this paper, backstepping and adaptive dynamical sliding mode control is used to achieve chaos synchronization of coupled FitzHugh-Nagumo (FHN) neurons. The proposed controller consists of a combination of dynamical sliding mode control and adaptive backstepping technique. Based on a new switching function, the combined algorithm yields a design of dynamical sliding mode control law, which can realize chaos synchronization of coupled FHN neurons with uncertain parameters. It is shown that the proposed approach can effectively remove the chattering characteristic of the system, so that the intrinsic dynamics of neurons can avoid to be destroyed. Furthermore, it has rapid control performance. The simulation results have demonstrated the effectiveness of the control scheme.
Keywords： adaptive dynamical sliding mode control FitzHugh-Nagumo neuron chaos synchronization