Citation
Mehdi Maasoumy, Alberto Sangiovanni-Vincentelli. "Computationally Less Intensive Alternative to Model Predictive Control for Energy Efficient Building HVAC System". ACM Symposium on Simulation for Architecture and Urban Design (SimAUD), 13, April, 2014.

Abstract
A framework for the design and simulation of a building envelope and an HVAC system is presented. Building models are first captured in Modelica to leverage its rich building component library and then imported into Simulink to exploit its strong control design environment that enables efficient control design and implementation. Four controllers with different computational intensity are considered and compared: a proportional (P) controller with time varying temperature bounds, a tracking LQR controller with time varying tuning parameters, a tracking d-LQR controller with time varying tuning parameters which incorporates the predictive disturbance information in control derivation and a model predictive controller (MPC).We assess the performance of these controllers using two defined criteria, i.e. energy and discomfort indices. We show that the d-LQR and MPC compared to the P control, manage to reduce the energy index by 41.2% and 46% respectively, and the discomfort index from 3.8 to 0. While d-LQR and MPC have similar performance concerning energy and discomfort index, simulation time in the case of d-LQR is significantly less than that of MPC.

Electronic downloads

• https://www.src.org/library/publication/p069387/
• http://www.eecs.berkeley.edu/~maasoumy/Research_files/IGESC_Computation.pdf

• HTML

  Mehdi Maasoumy, Alberto Sangiovanni-Vincentelli. <a
  href="http://www.terraswarm.org/pubs/255.html"
  >Computationally Less Intensive Alternative to Model
  Predictive Control for Energy Efficient Building HVAC
  System</a>, ACM Symposium on Simulation for
  Architecture and Urban Design (SimAUD), 13, April, 2014.

• Plain text

  Mehdi Maasoumy, Alberto Sangiovanni-Vincentelli.
  "Computationally Less Intensive Alternative to Model
  Predictive Control for Energy Efficient Building HVAC
  System". ACM Symposium on Simulation for Architecture
  and Urban Design (SimAUD), 13, April, 2014.

• BibTeX

  @inproceedings{MaasoumySangiovanniVincentelli14_ComputationallyLessIntensiveAlternativeToModelPredictive,
      author = {Mehdi Maasoumy and Alberto Sangiovanni-Vincentelli},
      title = {Computationally Less Intensive Alternative to
                Model Predictive Control for Energy Efficient
                Building HVAC System},
      booktitle = {ACM Symposium on Simulation for Architecture and
                Urban Design (SimAUD)},
      day = {13},
      month = {April},
      year = {2014},
      abstract = {A framework for the design and simulation of a
                building envelope and an HVAC system is presented.
                Building models are first captured in Modelica to
                leverage its rich building component library and
                then imported into Simulink to exploit its strong
                control design environment that enables efficient
                control design and implementation. Four
                controllers with different computational intensity
                are considered and compared: a proportional (P)
                controller with time varying temperature bounds, a
                tracking LQR controller with time varying tuning
                parameters, a tracking d-LQR controller with time
                varying tuning parameters which incorporates the
                predictive disturbance information in control
                derivation and a model predictive controller
                (MPC).We assess the performance of these
                controllers using two defined criteria, i.e.
                energy and discomfort indices. We show that the
                d-LQR and MPC compared to the P control, manage to
                reduce the energy index by 41.2% and 46%
                respectively, and the discomfort index from 3.8 to
                0. While d-LQR and MPC have similar performance
                concerning energy and discomfort index, simulation
                time in the case of d-LQR is significantly less
                than that of MPC.},
      URL = {http://terraswarm.org/pubs/255.html}
  }
  

Posted by Mehdi Maasoumy on 10 Feb 2014.