Application of adaptive multivariable Generalized Predictive Control to a HVAC system in real time

• Autorzy: Gulan M. , Salaj M. , Rohal’-Ilkiv B

Identyfikatory

DOI

10.2478/acsc-2014-0005

• Języki publikacji: EN

Abstrakty

EN

This paper presents the application of a Multivariable Generalized Predictive Controller (MGPC) for simultaneous temperature and humidity control in a Heating, Ventilating and Air- Conditioning (HVAC) system. The multivariable controlled process dynamics is modeled using a set of MISO models on-line identified from measured input-output process data. The controller synthesis is based on direct optimization of selected quadratic cost function with respect to amplitude and rate input constraints. Efficacy of the proposed adaptive MGPC algorithm is experimentally demonstrated on a laboratory-scale model of HVAC system. To control the airconditioning part of system the designed multivariable predictive controller is considered in a cascade dual-rate control scheme with PID auxiliary controllers.

Słowa kluczowe

EN

predictive control; multivariable systems; constrained optimization; HVAC system; cascade control

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2014
• Tom: Vol. 24, no. 1
• Strony: 67--84
• Opis fizyczny: Bibliogr. 19 poz., rys., wzory

Twórcy

autor

Gulan M.

• Institute of Automation, Measurement and Applied Informatics, Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava, Nám. slobody 17, 812 31 Bratislava, Slovakia

autor

Salaj M.

• Institute of Automation, Measurement and Applied Informatics, Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava, Nám. slobody 17, 812 31 Bratislava, Slovakia

autor

Rohal’-Ilkiv B

• Institute of Automation, Measurement and Applied Informatics, Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava, Nám. slobody 17, 812 31 Bratislava, Slovakia

Bibliografia

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Uwagi

The paper was created with the support of the Ministry of Education, Science, Research and Sport of the Slovak Republic within the Research and Development Operational Programme for the project ”University Science Park of STU Bratislava”, ITMS 26240220084, co-funded by the European Regional Development Fund.