US 11,886,153 B2
Building control system using reinforcement learning
Sugumar Murugesan, Santa Clara, CA (US); Young M. Lee, Old Westbury, NY (US); and Viswanath Ramamurti, San Leandro, CA (US)
Assigned to JOHNSON CONTROLS TYCO IP HOLDINGS LLP, Milwaukee, WI (US)
Filed by Johnson Controls Tyco IP Holdings LLP, Milwaukee, WI (US)
Filed on Jul. 22, 2021, as Appl. No. 17/383,213.
Claims priority of provisional application 63/055,781, filed on Jul. 23, 2020.
Prior Publication US 2022/0026864 A1, Jan. 27, 2022
Int. Cl. G05B 13/04 (2006.01); H02J 3/00 (2006.01); G06N 3/08 (2023.01); G05B 13/02 (2006.01); G06N 3/045 (2023.01)
CPC G05B 13/048 (2013.01) [G05B 13/027 (2013.01); G05B 13/041 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); H02J 3/003 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A building management system, comprising:
one or more memory devices configured to store instructions thereon that, when executed by one or more processors, cause the one or more processors to:
determine policy rankings for a plurality of control policies based on building operation data of a first previous time period;
select a set of control policies from among the plurality of control policies based on the policy rankings of the set of control policies satisfying a ranking threshold;
generate a plurality of prediction models for the set of control policies;
select a first prediction model of the plurality of prediction models based on building operation data of a second previous time period; and
responsive to selecting the first prediction model, operate the building management system using the first prediction model.