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相关概念视频

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Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
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The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
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采用Ridge-momentum回归和基于网格的结构优化的通风空气的模型识别

Cong Toai Truong1,2, Trung Dat Phan1,2, Van Tu Duong1,2

  • 1Key Laboratory of Digital Control and System Engineering (DCSELab), Faculty of Mechanical Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam.

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概括

这项研究引入了一种新的方法,即用动量修改的Ridge回归 (Ridge-M),用于识别机械呼吸机中的模型. Ridge-M 提高了通风参数的稳定性和准确性,这对于呼吸系统的流行病准备非常重要.

关键词:
一个ARMA模型边缘回归网格搜索模型识别动量

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科学领域:

  • 工程
  • 控制系统
  • 生物医学工程

背景情况:

  • 机械呼吸器在流行病期间对呼吸系统的支持至关重要.
  • 由于系统的不确定性和时间变化的参数,对通风机发电单元的准确建模存在挑战.
  • 现有的建模技术面临复杂的动态和有限的计算资源.

研究的目的:

  • 开发一种新且强大的算法,用于识别通风中的自行回归移动平均值 (ARMA) 模型.
  • 增强模型识别稳定性和适应时间变化的系统.
  • 优化ARMA模型订单和时间延迟参数的选择.

主要方法:

  • 用动量修改的Ridge回归的实施 (Ridge-M).
  • 整合一个网格搜索策略,以共同优化模型订单和时间延迟.
  • 使用Akaike信息标准 (AIC) 进行模型结构选择.
  • 使用道和多步进口信号进行实验验证.

主要成果:

  • 与递归最小方程 (RLS) 和标准的Ridge回归相比,Ridge-M在捕捉动态系统行为方面表现出更好的表现.
  • 对于多步入的输入,Ridge- M实现了比RLS平均2. 7%和比标准Ridge回归平均6. 8%的根平均平方误差 (RMSE) 降低.
  • 标准Ridge回归显示了坡道输入的轻微优势,而Ridge-M则产生了最低的整体平均RMSE (31.6236).

结论:

  • 拟议的Ridge-M算法提供了一种稳定且可适应的机械呼吸机模型识别方法.
  • 这种方法适用于带有噪音数据,时间变化的系统和有限的计算能力的嵌入式应用程序.
  • 这些发现有助于提高基本呼吸器设备的可靠性和性能.