Adaptive supervisory tuning of nonlinear model predictive controller for a heat exchanger

Margarita Terziyska, Yancho Todorov, Michail Petrov

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

4 Citations (Scopus)

Abstract

It is presented in this paper an adaptive predictive supervisory algorithm to the temperature control of a heating system with a heat exchanger. The nonlinear predictive control strategy is designed on the basis of a Takagi-Sugeno fuzzy-neural model and a simple optimization procedure. An additional supervisory level in the control system is introduced for adaptive tuning of a weighting factor in the predefined optimization criterion. Using the proposed algorithm a higher system performance can be achieved which leads to reduction of the energy consumption into the heating system. The proposed approach is studied by experimental simulations to control a temperature in the heating system.

Original languageEnglish
Title of host publication1st IFAC Workshop on Energy Saving Control in Plants and Buildings
PublisherElsevier
Pages93-98
ISBN (Print)978-3-902661-19-7
DOIs
Publication statusPublished - 1 Dec 2006
MoE publication typeA4 Article in a conference publication
EventInternational IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006 - Bansko, Bulgaria
Duration: 2 Oct 20065 Oct 2006

Publication series

SeriesIFAC Proceedings Volumes
Number19
Volume39
ISSN1474-6670

Conference

ConferenceInternational IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006
CountryBulgaria
CityBansko
Period2/10/065/10/06

Keywords

  • Fuzzy control
  • Heating systems
  • Predictive control

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