Approximate Dynamic Programming for Building Control Problems with Occupant Interactions

被引：0
|
作者：
Lee, Donghwan [1 ]
Lee, Seungjae [2 ]
Karava, Panagiota [2 ]
Hu, Jianghai [3 ]
机构：
[1] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL 61801 USA
[2] Purdue Univ, Dept Civil Engn, W Lafayette, IN 47906 USA
[3] Purdue Univ, Dept Elect & Comp Engn, W Lafayette, IN 47906 USA
来源：
2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | 2018年
基金：
美国国家科学基金会;
关键词：
REINFORCEMENT LEARNING CONTROL; MODEL-PREDICTIVE CONTROL; STOCHASTIC-MODEL; ENERGY; SIMULATION; SYSTEMS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The goal of this paper is to study potential applicability and performance of approximate dynamic programming (ADP) for building control problems. It is well known that occupants' stochastic behavior affects the thermal dynamics of building spaces. Incorporating occupant interactions in building control system designs is the main focus of this work. We apply ADP to stochastic optimal control designs for illustrative scenarios of occupant-building interactions and demonstrate its validity through a simulation study.
引用
收藏
页码：3945 / 3950
页数：6
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