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相关概念视频

Neural Control of Respiration01:18

Neural Control of Respiration

The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
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相关实验视频

Updated: May 8, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
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通过自适应神经固定时间控制,用于网络异质机器人系统的任务空间跟踪.

Ren-Jie Gu1, Tao Han1, Bo Xiao1

  • 1School of Electrical Engineering and Automation, Hubei Normal University, Huangshi 435005, PR China.

ISA transactions
|October 2, 2024
PubMed
概括

本研究介绍了一种用于网络异质机器人系统 (NHRSs) 的新型神经网络 (NN) 控制方法. 它通过解决不确定性和提高趋同速度来确保固定时间跟踪.

关键词:
固定时间层次控制 (FTHC)网络化异质机器人系统 (NHRSs)神经网络 (NN) 是一个神经网络.追踪控制系统的追踪控制系统

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相关实验视频

Last Updated: May 8, 2026

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 控制系统 控制系统
  • 人工智能的人工智能

背景情况:

  • 网络异质机器人系统 (NHRSs) 提出了复杂的控制挑战.
  • 固定时间跟踪对于精确的机器人操作至关重要.

研究的目的:

  • 为NHRSs开发基于神经网络 (NN) 的固定时间层次控制方法.
  • 解决任务空间分布的自适应NN固定时间跟踪问题.

主要方法:

  • 一种分层的控制策略,将问题分解为分布式估计和局部跟踪.
  • 使用神经网络 (NN) 来近似复合不确定性.
  • 设计一个自适应的神经固定时间本地跟踪控制器.

主要成果:

  • 分布式估计器使追随者能够在固定的时间内获得领导者状态.
  • 无线网络有效地接近未知的动态和干扰.
  • 拟议的控制器确保追踪错误的固定时间融合,独立于初始状态.

结论:

  • 基于NN的固定时间层次控制方法对NHRSs有效.
  • 该方法通过对近似误差的新处理来提高稳定性和趋同速度.
  • 实验结果验证了拟议的控制方法的优势.