Learning Control for Air Conditioning Systems via Human Expressions
Wei, Qinglai1,2,3; Li, Tao1,2,3; Liu, Derong4
Source PublicationIEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
ISSN0278-0046
2021-08-01
Volume68Issue:8Pages:7662-7671
Corresponding AuthorWei, Qinglai(qinglai.wei@ia.ac.cn)
AbstractIn this article, a deep reinforcement learning method is developed to solve air conditioning control problems through human expressions. The main contribution of this article is to design a deep reinforcement learning method for air conditioning control problems with human expressions as the input for the first time. The method aims to eliminate human sleepiness and improve people's work efficiency as much as possible. First, the air conditioning system and deep reinforcement learning methods are introduced. Second, the image processing algorithm for human expressions is described. Third, the deep Q-network method is designed to obtain the optimal control policy for air conditioning systems. Finally, simulation results are given to illustrate the present method that can effectively eliminate sleepiness and improve the work environment of people.
KeywordAdaptive dynamic programming air conditioning control deep learning (DL) deep Q-network (DQN) human expressions optimal control reinforcement learning (RL) Q-learning
DOI10.1109/TIE.2020.3001849
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61722312] ; National Natural Science Foundation of China[61533017] ; National Key Research and Development Program of China[2018YFB1702300]
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000647484000120
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:28[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44655
Collection复杂系统管理与控制国家重点实验室_复杂系统智能机理与平行控制团队
Corresponding AuthorWei, Qinglai
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
4.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wei, Qinglai,Li, Tao,Liu, Derong. Learning Control for Air Conditioning Systems via Human Expressions[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2021,68(8):7662-7671.
APA Wei, Qinglai,Li, Tao,&Liu, Derong.(2021).Learning Control for Air Conditioning Systems via Human Expressions.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,68(8),7662-7671.
MLA Wei, Qinglai,et al."Learning Control for Air Conditioning Systems via Human Expressions".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 68.8(2021):7662-7671.
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