Advanced control strategies for heating, ventilation, air-conditioning, and refrigeration systems-An overview: Part I: Hard control

被引:62
作者
Naidu, D. Subbaram [1 ]
Rieger, Craig G. [2 ]
机构
[1] Idaho State Univ, Dept Elect Engn & Comp Sci, Sch Engn, Pocatello, ID 83209 USA
[2] Idaho Natl Lab, Idaho Falls, ID 83415 USA
来源
HVAC&R RESEARCH | 2011年 / 17卷 / 01期
关键词
MODEL-PREDICTIVE CONTROL; REINFORCEMENT LEARNING CONTROL; NEAR-OPTIMAL CONTROL; HVAC SYSTEMS; ROBUST-CONTROL; FEEDBACK LINEARIZATION; DECENTRALIZED CONTROL; TEMPERATURE CONTROL; ENERGY MANAGEMENT; NONLINEAR CONTROL;
D O I
10.1080/10789669.2011.540942
中图分类号
O414.1 [热力学];
学科分类号
摘要
A chronological overview of the advanced control strategies for heating, ventilation, air-conditioning, and refrigeration (HVAC&R) is presented in this article. The overview focuses on hard-computing or control techniques, such as proportional-integral-derivative, optimal, nonlinear, adaptive, and robust; soft-computing or control techniques, such as neural networks, fuzzy logic, genetic algorithms; and on the fusion or hybrid of hard- and soft-control techniques. Thus, it is to be noted that the terminology "hard" and "soft" computing/control has nothing to do with the "hardware" and "software" that is being generally used. Part I of a two-part series focuses on hard-control strategies, and Part II focuses on soft- and fusion-control in addition to some future directions in HVAC&R research. This overview is not intended to be an exhaustive survey on this topic, and any omission of other works is purely unintentional.
引用
收藏
页码:2 / 21
页数:20
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