Learning/repetitive control for building systems with nearly periodic disturbances

Kasper Vinther, Vikas Chandan, Andrew G. Alleyne

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, learning/repetitive control is proposed for improvement of existing feedback control loops for temperature regulation in buildings. A single zone office building is used as an example, with real weather data for Phoenix Arizona and realistic occupancy load schedules. Simulations have shown a decrease in the average set point tracking error of more than 50%, even without additional energy consumption. This can be achieved in situations where the load disturbances have enough repeatability and a repeatable-to-nonrepeatable ratio can be computed to determine if learning should be used and at which frequencies. Furthermore, the increased tightness in reference tracking could be used to lower energy consumption by moving the reference set point closer to the boundaries of the allowable temperature range.

Original languageEnglish (US)
Title of host publication2013 European Control Conference, ECC 2013
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)9783033039629
StatePublished - 2013
Event2013 12th European Control Conference, ECC 2013 - Zurich, Switzerland
Duration: Jul 17 2013Jul 19 2013

Publication series

Name2013 European Control Conference, ECC 2013


Other2013 12th European Control Conference, ECC 2013

ASJC Scopus subject areas

  • Control and Systems Engineering


Dive into the research topics of 'Learning/repetitive control for building systems with nearly periodic disturbances'. Together they form a unique fingerprint.

Cite this