Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

Rui Mirra Santos, Yi Zong, Joao M. C. Sousa, Luis Mendonca, Shi You, Lucian Mihet-Popa

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy filtering, is performed. The results show that the controller achieves a good performance while keeping the temperature inside the predefined comfort limits. Fuzzy predictive filtering has shown to be an effective tool which is capable of reducing the computational burden and increasing the performance level of the control algorithm.
Original languageEnglish
Title of host publicationProceedings of 2016 IEEE Electrical Power and Energy Conference
Number of pages6
PublisherIEEE
Publication date2016
Pages1-6
ISBN (Print)9781509019199
DOIs
Publication statusPublished - 2016
EventIEEE Electrical Power and Energy Conference 2016 - Ottawa, Canada
Duration: 12 Oct 201614 Oct 2016

Conference

ConferenceIEEE Electrical Power and Energy Conference 2016
CountryCanada
CityOttawa
Period12/10/201614/10/2016
Series2016 Ieee Electrical Power and Energy Conference (epec)

Keywords

  • Optimization
  • Buildings
  • Resistance heating
  • Computational modeling
  • Aerospace electronics
  • Predictive models
  • smart buildings
  • Branch-and-bound optimization
  • demand response
  • fuzzy predictive filtering
  • nonlinear economic model predictive control

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