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首页> 外文期刊>Neural computation >Robust Observer-Based Tracking Control of Hodgkin-Huxley Neuron Systems Under Environmental Disturbances
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Robust Observer-Based Tracking Control of Hodgkin-Huxley Neuron Systems Under Environmental Disturbances

机译:基于扰动的霍奇金-赫克斯利神经元系统在环境扰动下的跟踪控制

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摘要

A nervous system consists of a large number of highly interconnected nerve cells. Nerve cells communicate by generation and transmission of short electrical pulses (action potential). In addition, membrane voltage is the only measurable state in nervous systems. A robust observer-based model reference tracking control is proposed for Hodgkin-Huxley (HH) neuron systems to generate a desired reference response in spite of environmental noises, uncertain initial values, and diffusion currents from other interconnected nerve cells. In order to simplify the robust tracking control design of nonlinear stochastic HH neuron systems, a fuzzy interpolation method is employed to interpolate several linear stochastic systems to approximate a nonlinear stochastic HH neuron system so that the nonlinear robust tracking control problem can be solved by the linear matrix inequality (LMI) technique with the help of Robust Control Toolbox in Matlab. The proposed robust observer-based tracking control scheme can provide new methods for desired action potential generation, suppression of oscillations, and blockage of action potential transmission under environmental noise and diffusion currents. These new methods are useful for patients with different neuron system dysfunctions. Finally, three simulation examples of tracking control of nervous systems are given to illustrate the design procedure and confirm the tracking performance of the proposed method.
机译:神经系统由大量高度互连的神经细胞组成。神经细胞通过产生和传输短电脉冲(动作电位)进行通信。此外,膜电压是神经系统中唯一可测量的状态。针对霍奇金-赫克斯利(HH)神经元系统,提出了一种鲁棒的基于观察者的模型参考跟踪控制,以产生期望的参考响应,尽管存在环境噪声,不确定的初始值以及来自其他互连神经细胞的扩散电流。为了简化非线性随机HH神经元系统的鲁棒跟踪控制设计,采用模糊插值法对多个线性随机系统进行插值以逼近非线性随机HH神经元系统,从而可以通过线性求解来解决非线性鲁棒跟踪控制问题。借助Matlab中的稳健控制工具箱,实现了矩阵不等式(LMI)技术。所提出的基于观测器的鲁棒鲁棒跟踪控制方案可以为在环境噪声和扩散电流下产生所需的动作电位,抑制振荡以及阻止动作电位的传输提供新的方法。这些新方法对具有不同神经系统功能障碍的患者很有用。最后,给出了三个神经系统跟踪控制的仿真例子,说明了该程序的设计过程,并验证了该方法的跟踪性能。

著录项

  • 来源
    《Neural computation》 |2010年第12期|p.3143-3178|共36页
  • 作者

    Bor-Sen Chen; Cheng-Wei Li;

  • 作者单位

    Laboratory of Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan;

    rnLaboratory of Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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