Approximate optimal iterative approach for a class of oscillatory neuron models

被引:0
|
作者
Lou, Xuyang [1 ]
Ye, Qian [2 ]
机构
[1] Jiangnan Univ, Inst Syst Engn, Wuxi, Peoples R China
[2] Wuxi Inst Technol, Wuxi, Peoples R China
来源
SYSTEMS SCIENCE & CONTROL ENGINEERING | 2018年 / 6卷 / 01期
基金
中国国家自然科学基金;
关键词
FitzHugh-Nagumo model; optimal control; approximate optimal iterative approach; oscillatory neuron;
D O I
10.1080/21642583.2018.1547882
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Control of oscillatory neuron models becomes a growing interest due to the application of implanted stimulus electrodes in mitigating pathological behaviours. We present an approximate optimal iterative control method for minimum-current control of the FitzHugh-Nagumo model with external disturbance. We first focus on revealing optimality conditions based on the Pontryagin's maximum principle and constructing a related nonlinear two-point boundary value problem. Then, we transform the problem into two iterative sequences of linear differential equations. The control law is finally derived and composed of feedback and compensation terms which can be approximated using approximate iterative approach. Simulations illustrate the results.
引用
收藏
页码:518 / 527
页数:10
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