Intelligent and adaptive temperature control for large-scale buildings and homes

Yuan Wang, Partha Dasgupta

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

1 Scopus citations

Abstract

Temperature control in smart buildings and homes can be automated by having computer controlled air-conditioning systems along with temperature sensors that are distributed in the controlled area. However, programming actuators in large-scale buildings and homes can be time consuming and expensive. We present an approach that algorithmically sets up the control system that can generate optimal actuator settings for large-scale environments. This paper clearly describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner(AC) on each sensor at a particular time is learnt using linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comforts and low cost of energy consumptions. Our method works as generic control algorithms and are not preprogrammed for a particular place. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency for temperature control. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.

Original languageEnglish (US)
Title of host publicationICNSC 2016 - 13th IEEE International Conference on Networking, Sensing and Control
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467399753
DOIs
StatePublished - May 25 2016
Event13th IEEE International Conference on Networking, Sensing and Control, ICNSC 2016 - Mexico City, Mexico
Duration: Apr 28 2016Apr 30 2016

Other

Other13th IEEE International Conference on Networking, Sensing and Control, ICNSC 2016
CountryMexico
CityMexico City
Period4/28/164/30/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Control and Systems Engineering
  • Modeling and Simulation

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