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闫秀英

副教授   硕士生导师

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  • 教师拼音名称: yanxiuying
  • 所在单位: 建筑设备科学与工程学院
  • 性别: 女
  • 在职信息: 在职
  • 主要任职: 副教授
  • 其他任职: 陕西省自动化学会计算机应用分会委员

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论文成果

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Iterative Learning Control in Large Scale HVAC System

发布时间:2024-08-09
点击次数:
所属单位:
建筑设备科学与工程学院
发表刊物:
The 8th World Congress on Intelligent Control and Automation
关键字:
中文关键字:wu,英文关键字:variable air volume. iterative learning control;la
摘要:
Heating, ventilating and air-conditioning (HVAC) system is a multi-variable, strongly coupled, nonlinear, time variant, large time delay and large-scale system composed of several subsystems. In order to save energy, all the subsystems should work coordinately in different working points to meet the people’s comfortable requirement. In HVAC control systems, system optimal control inputs or optimal operating points, which can be acquired through supervisory and optimal control, can ensure minimum energy cost and satisfy indoor comfort and air quality, taking into account the ever-changing indoor and outdoor conditions as well as the characteristics of HVAC systems. A variable air volume (VAV) variable water volume (VWV) air-conditioning system is wholly analyzed with large- scale system theory based on “decomposition and coordination” strategy. Iterative learning control (ILC) strategy is introduced first into a large-scale HVAC system, and the effectiveness of the ILC strategy is demonstrated through a case study. Results show that as the number of iteration increases, the system tracking error over the entire operation will decrease and eventually vanish. This means that the good performance of subsystems can be maintained under the ILC strategy when the working points change with the dynamic load.
备注:
闫秀英
第一作者:
任庆昌,闫秀英
论文类型:
期刊论文
卷号:
卷:
期号:
期:
页面范围:
页:5063-5066
是否译文:
发表时间:
2010-07-01