Selecting building predictive control based on model uncertainty
Document Type
Conference Proceeding
Publication Date
1-1-2014
Abstract
Model uncertainty limits the utilization of Model Predictive Controllers (MPC) to minimize building energy consumption. We propose a new Robust Model Predictive Control (RMPC) structure to make a building controller robust to model uncertainty. The results from RMPC are compared with those from a nominal MPC and a common building Rule Based Control (RBC). The results are then used to develop a methodology for selecting a controller type (i.e. RMPC, MPC, and RBC) as a function of building model uncertainty. RMPC is found to be the desirable controller for the cases with an intermediate level (30%-67%) of model uncertainty, while MPC is preferred for the cases with a low level (0-30%) of model uncertainty. A common RBC is found to outperform MPC or RMPC if the model uncertainty goes beyond a certain threshold (e.g. 67%). © 2014 American Automatic Control Council.
Publication Title
Proceedings of the American Control Conference
Recommended Citation
Maasoumy, M.,
Razmara, M.,
Shahbakhti, M.,
&
Sangiovanni Vincentelli, A.
(2014).
Selecting building predictive control based on model uncertainty.
Proceedings of the American Control Conference, 404-411.
http://doi.org/10.1109/ACC.2014.6858875
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10275