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Authors: Nsilulu T. Mbungu 1 ; 2 ; 3 ; Raj M. Naidoo 3 ; Ramesh C. Bansal 1 and Mukwanga W. Siti 2

Affiliations: 1 Department of Electrical and Computer Engineering, University of Sharjah, Sharjah, U.A.E. ; 2 Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa ; 3 Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, South Africa

Keyword(s): Energy Efficiency, Model Predictive Control, Optimal Control, Power System, Demand Response.

Abstract: This paper presents the structure of the model predictive control (MPC), its development and application through optimal energy system. The MPC is one of the algorithms that are used in a computer controlled environment to predict the future behaviour of an explicit process model. It is devised by computing and adjusting the next sequence of the input variables at each control interval. The MPC is an algorithm in which the challenge is to optimize the behaviour of a future plant. The optimization sequence starts by sending the first input into the plant and then at each subsequent control interval the entire computation is repeated to reach the performance index function to follow. MPC offers a variety of applications in a wide range of industries. This is due to its robustness in the optimal control design of a process. MPC is also widely used in aerospace, automotive, chemical and food processing applications. This study describes the implementation of the energy management scheme through the use of MPC design. (More)

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Paper citation in several formats:
Mbungu, N.; Naidoo, R.; Bansal, R. and Siti, M. (2021). Model Predictive Control: A Survey of Dynamic Energy Management. In Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - ICINCO; ISBN 978-989-758-522-7; ISSN 2184-2809, SciTePress, pages 123-129. DOI: 10.5220/0010522201230129

@conference{icinco21,
author={Nsilulu T. Mbungu. and Raj M. Naidoo. and Ramesh C. Bansal. and Mukwanga W. Siti.},
title={Model Predictive Control: A Survey of Dynamic Energy Management},
booktitle={Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - ICINCO},
year={2021},
pages={123-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010522201230129},
isbn={978-989-758-522-7},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - ICINCO
TI - Model Predictive Control: A Survey of Dynamic Energy Management
SN - 978-989-758-522-7
IS - 2184-2809
AU - Mbungu, N.
AU - Naidoo, R.
AU - Bansal, R.
AU - Siti, M.
PY - 2021
SP - 123
EP - 129
DO - 10.5220/0010522201230129
PB - SciTePress