Journal article
Guest Editorial Model Predictive Control in Energy Conversion Systems
Department of Electrical Engineering, Technical University of Denmark1
Columbia University2
University of Kurdistan3
University of Oxford4
Electronics, Department of Electrical Engineering, Technical University of Denmark5
Center for Electric Power and Energy, Centers, Technical University of Denmark6
Smart Electric Components, Center for Electric Power and Energy, Centers, Technical University of Denmark7
University of Manchester8
Universidad Andrés Bello9
Swiss Federal Institute of Technology Lausanne10
Paderborn University11
Polytechnic University of Milan12
...and 2 moreThe papers in this special section focus on model predictive control (MPC) in energy conversion systems. MPC refers to a broad range of control strategies that make explicit use of a model of the system/device to be controlled optimally. In order to obtain the optimal control signal (or sequence of control signals), MPC optimizes a certain cost function at regular intervals.
Due to its unique capabilities to deal with constraints on actuators and system states as well as its theoretical basis, MPC has been widely received and successfully used for many decades, mostly for control of slow industrial plants. However, with continuous advances of control theory and increasing computational capabilities of modern microprocessors, this control strategy has recently became a technically feasible solution for control of energy conversion systems that operate at much faster times scales.
Language: | English |
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Publisher: | IEEE |
Year: | 2021 |
Pages: | 1311-1312 |
ISSN: | 15580059 and 08858969 |
Types: | Journal article |
DOI: | 10.1109/TEC.2021.3076279 |
ORCIDs: | Dragicevic, Tomislav , 0000-0001-8633-1641 , 0000-0002-1410-4121 , 0000-0001-7239-4799 , 0000-0002-4804-5481 , 0000-0001-7598-8971 , 0000-0002-6713-2978 , 0000-0001-9529-7350 and 0000-0003-2781-9588 |