Citation
Mehdi Maasoumy, Meysam Razmara, Mahdi Shahbakhti, Alberto Sangiovanni-Vincentelli. "Selecting Building Predictive Control Based on Model Uncertainty". IEEE American Control Conference, 4, June, 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%).

Electronic downloads

• https://www.src.org/library/publication/p069386/. (Link to publication on SRC website.)
• http://dx.doi.org/10.1109/ACC.2014.6858875

• HTML

  Mehdi Maasoumy, Meysam Razmara, Mahdi Shahbakhti, Alberto
  Sangiovanni-Vincentelli. <a
  href="http://www.terraswarm.org/pubs/258.html"
  >Selecting Building Predictive Control Based on Model
  Uncertainty</a>, IEEE American Control Conference, 4,
  June, 2014.

• Plain text

  Mehdi Maasoumy, Meysam Razmara, Mahdi Shahbakhti, Alberto
  Sangiovanni-Vincentelli. "Selecting Building Predictive
  Control Based on Model Uncertainty". IEEE American
  Control Conference, 4, June, 2014.

• BibTeX

  @inproceedings{MaasoumyRazmaraShahbakhtiSangiovanniVincentelli14_SelectingBuildingPredictiveControlBasedOnModelUncertainty,
      author = {Mehdi Maasoumy and Meysam Razmara and Mahdi
                Shahbakhti and Alberto Sangiovanni-Vincentelli},
      title = {Selecting Building Predictive Control Based on
                Model Uncertainty},
      booktitle = {IEEE American Control Conference},
      day = {4},
      month = {June},
      year = {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%).},
      URL = {http://terraswarm.org/pubs/258.html}
  }
  

Posted by Mehdi Maasoumy on 10 Feb 2014.