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2020 | OriginalPaper | Chapter

2. Model Predictive Control Fundamentals

Authors : Carlos Bordons, Félix Garcia-Torres, Miguel A. Ridao

Published in: Model Predictive Control of Microgrids

Publisher: Springer International Publishing

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Abstract

This book is focused on Model Predictive Control (MPC) techniques, which will be used to solve different control issues in microgrids. Although there are many techniques that can be used for the control of microgrids, MPC provides a general framework to solve most of the issues using some common ideas in an integrated way. MPC replaces offline determination of a control law by online solution of an optimal control problem that provides the current control action. This chapter presents the fundamentals of this technique. The main ideas and formulations are described here as well as some of the most representative techniques. MPC based on state-space models is detailed, since it will be extensively used along the book. Other techniques such as finite state MPC and MPC for hybrid systems are described too. The chapter also tackles two important issues for the application of MPC in microgrids: disturbances and constraints. Based on the methods presented in this chapter, the most relevant topics related to the control of microgrids will be addressed along the rest of the book.

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Footnotes
1
The notation indicates the value of the variable at the instant \(t+k\) calculated at the current instant t.
 
2
Defined as \(\Vert x\Vert _R ^{2}=x^T R x.\)
 
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Metadata
Title
Model Predictive Control Fundamentals
Authors
Carlos Bordons
Félix Garcia-Torres
Miguel A. Ridao
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-24570-2_2