一种容错控制策略,用于估计和补偿超市制冷系统中的温度传感器偏差
Patrick Haffmans1, Roozbeh Izadi-Zamanabadi2, Hossein Ramezani1
1University of Southern Denmark, Denmark.
ISA transactions
|November 3, 2023
概括
本研究介绍了一种数据驱动的容错控制 (FTC) 策略,用于管理超市制冷中的环境温度传感器偏差. 该方法显著降低了能源消耗,特别是在夏季.
科学领域:
- 制冷系统工程 制冷系统工程
- 控制系统理论 控制系统理论
- 数据驱动建模数据驱动建模
背景情况:
- 超市制冷系统中的环境温度传感器偏差,通常是由阳光照射引起的,显著影响能源消耗.
- 准确的温度监测对于商业制冷的高效运行和食品安全至关重要.
研究的目的:
- 开发和验证数据驱动的容错控制 (FTC) 策略,以解决环境温度传感器偏差的问题.
- 量化可通过拟议的FTC战略实现的节能.
主要方法:
- 使用真实世界的数据分析开发了一个全面的偏见模型.
- 在FTC战略中,Feedforward神经网络 (NN) 被用作黑盒模型.
- 在非高峰 (夜间) 操作期间,NN模型使用扰动信号进行训练.
主要成果:
- 拟议的FTC战略成功地适应了环境温度传感器偏差.
- 蒙特卡洛的模拟表明了Plug & Play实施的有效性.
- 实现了大量的能源节约,特别是在夏季运行期间.
结论:
- 数据驱动的FTC战略为冷却系统中传感器偏差管理提供了有效的解决方案.
- 基于神经网络的方法为故障耐受性提供了强大的和可适应的方法.
- 实施这一战略导致超市制冷系统的能源效率大幅提高.
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