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
相关论文
共 50 条
  • [1] Approximate Optimal Tracking Control for a Class of Nonlinear Systems
    Fan, Ming-Qu
    Tang, Gong-You
    2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 946 - 950
  • [2] An Approximate Optimal Control Approach for Robust Stabilization of a Class of Discrete-Time Nonlinear Systems With Uncertainties
    Wang, Ding
    Liu, Derong
    Li, Hongliang
    Luo, Biao
    Ma, Hongwen
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 46 (05): : 713 - 717
  • [3] Event-based minimum-time control of oscillatory neuron models
    Danzl, Per
    Hespanha, Joao
    Moehlis, Jeff
    BIOLOGICAL CYBERNETICS, 2009, 101 (5-6) : 387 - 399
  • [4] A parallel approach to improvement and estimation of the approximate optimal control
    Fesko, Oles
    JOURNAL OF COMPUTATIONAL SCIENCE, 2012, 3 (06) : 486 - 491
  • [5] Approximate solution of a class of optimal control problems in domains of arbitrary form
    Lyashko, II
    Lyashko, SI
    Voitsekhovskii, SA
    CYBERNETICS AND SYSTEMS ANALYSIS, 2000, 36 (01) : 108 - 117
  • [6] A Fast Iterative Approach for Optimal Control of Nonlinear Systems
    Liu, Jiaqi
    Dong, Shiying
    Hong, Jinlong
    Gao, Bingzhao
    Chen, Hong
    IFAC PAPERSONLINE, 2020, 53 (02): : 7049 - 7054
  • [7] Approximate solution of a class of optimal control problems in domains of arbitrary form
    I. I. Lyashko
    S. I. Lyashko
    S. A. Voitsekhovskii
    Cybernetics and Systems Analysis, 2000, 36 : 108 - 117
  • [8] A neural-network-based iterative GDHP approach for solving a class of nonlinear optimal control problems with control constraints
    Ding Wang
    Derong Liu
    Dongbin Zhao
    Yuzhu Huang
    Dehua Zhang
    Neural Computing and Applications, 2013, 22 : 219 - 227
  • [9] A neural-network-based iterative GDHP approach for solving a class of nonlinear optimal control problems with control constraints
    Wang, Ding
    Liu, Derong
    Zhao, Dongbin
    Huang, Yuzhu
    Zhang, Dehua
    NEURAL COMPUTING & APPLICATIONS, 2013, 22 (02) : 219 - 227
  • [10] Optimal Control for a Class of Unknown Nonlinear Systems via the Iterative GDHP Algorithm
    Wang, Ding
    Liu, Derong
    ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT II, 2011, 6676 : 630 - 639