%0 Journal Article
%A HU Lingyao1
%A 2
%A 3
%A CHEN Jianping1
%A 2
%A 3
%A FU Qiming1
%A 2
%A 3
%A 4
%A HU Wen1
%A 2
%A 3
%A NI Qingwen1
%A 2
%A 3
%T Building energy efficiency oriented reinforcement learning adaptive control method
%D 2017
%R 10.3778/j.issn.1002-8331.1702-0217
%J Computer Engineering and Applications
%P 239-246
%V 53
%N 21
%X With respect to the problem of slow convergence and instability for the traditional methods, in the field of building energy efficiency, this paper proposes a new reinforcement learning adaptive control method, RLAC by combining Q-learning. The proposed method models the exchange mechanism of the building energy consumption, and tries to find the better control policy by solving the optimal value function. Furthermore, RLAC can decrease the energy consumption without losing the performance of good comfort of the building occupants. Compared with the On/Off and Fuzzy-PD, the proposed RLAC has a better convergence performance in speed and accuracy.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1702-0217