Full Content is available to subscribers

Subscribe/Learn More  >

Automated Modeling of Building HVAC Systems for MPC

[+] Author Affiliations
Rohit H. Chintala, Christopher J. Bay, Bryan P. Rasmussen

Texas A&M University, College Station, TX

Paper No. DSCC2014-6224, pp. V001T07A005; 10 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 1: Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4618-6
  • Copyright © 2014 by ASME


Model predictive control (MPC) offers a tremendous scope in optimizing the consumption of energy by building HVAC systems. This paper presents an automated real-time procedure for the development of linear parametric models of building air-conditioning systems through system identification for the implementation of the MPC algorithms. The procedure is used to decide on the various aspects of system identification such as selecting the model structure, the inputs to the system, the interaction of the systems with their neighbors, and the updating of the model coefficients in real-time. The effectiveness of the procedure is demonstrated by modeling the various components air-conditioning systems of a real building. The root mean squared error was used as a performance metric to gauge the models. The paper also demonstrates that a 15 minute sampling interval is sufficient to model the dynamics of the air-handling unit and the room temperatures, but a faster sampling rate may be required to model the VAV boxes.

Copyright © 2014 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In