TR2019-056
Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump
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- "Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump", European Control Conference (ECC), DOI: 10.23919/ECC.2019.8795616, June 2019, pp. 1784-1789.BibTeX TR2019-056 PDF
- @inproceedings{Krupa2019jun,
- author = {Krupa, Pablo and Danielson, Claus and Laughman, Christopher R. and Bortoff, Scott A. and Burns, Daniel J. and Di Cairano, Stefano and Limon, Daniel},
- title = {Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump},
- booktitle = {18th European Control Conference (ECC)},
- year = 2019,
- pages = {1784--1789},
- month = jun,
- doi = {10.23919/ECC.2019.8795616},
- url = {https://www.merl.com/publications/TR2019-056}
- }
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- "Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump", European Control Conference (ECC), DOI: 10.23919/ECC.2019.8795616, June 2019, pp. 1784-1789.
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MERL Contacts:
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Research Areas:
Abstract:
This paper presents the design and realization of a linear Model Predictive Controller (MPC) and state estimator for a multi-zone heat pump in the Modelica modeling language, in order to validate closed-loop performance prior to experimental testing. The vapor compression system uses a variable speed compressor and a set of expansion valves for control, and it is required to regulate zone temperatures to set-points without offset. Constraints are imposed on all control inputs and also the values of both measured and unmeasured system outputs. Because experimental testing is both expensive and time-consuming, we have developed a tool chain for software-in-the-loop validation that uses a Modelica model for the plant, integrated with a software representation of the MPC that is realized in a combination of Modelica and C that is suitable for real-time use. We show the results of closedloop tests of the controller with a nonlinear system model, which provide a partial validation of the controller and tool chain.
Related News & Events
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NEWS MERL researchers presented more than 8 papers in European Control Conference, ECC 2019 Date: June 25, 2019 - June 28, 2019
Where: Naples, Italy
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Christopher R. Laughman; Daniel N. Nikovski; Diego Romeres; William S. Yerazunis
Research Areas: Control, Machine Learning, OptimizationBrief- The European Control Conference is the premier control conference in Europe. This year MERL was well represented with papers on control for HVAC, machine learning for estimation and control, robot assembly, and optimization methods for control.