A Sphere Decoding Algorithm for Multistep Sequential Model-Predictive Control

This article investigates the combination of two model-predictive control concepts, i.e., sequential model-predictive control and long-horizon model-predictive control, for power electronics. To achieve sequential model-predictive control, the optimization problem is split into two subproblems. The...

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Vydáno v:IEEE transactions on industry applications Ročník 57; číslo 3; s. 2931 - 2940
Hlavní autoři: Grimm, Ferdinand, Kolahian, Pouya, Zhang, Zhenbin, Baghdadi, Mehdi
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.05.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Control methods
Decoding
Electronics
Finite control set
Horizon
long horizon
Magnetic materials
Mathematical models
Mixed integer
model-predictive control (MPC)
Optimization
Permanent magnets
Photonic crystals
Prediction algorithms
Predictive control
Predictive models
sequential model-predictive control
sphere decoder
Wind turbines
ISSN:0093-9994, 1939-9367
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Shrnutí:This article investigates the combination of two model-predictive control concepts, i.e., sequential model-predictive control and long-horizon model-predictive control, for power electronics. To achieve sequential model-predictive control, the optimization problem is split into two subproblems. The first one summarizes all control goals, which linearly depend on the system inputs. Sequential model-predictive control generally requires to obtain more than one solution for the first subproblem. Due to the mixed-integer nature of finite control set model-predictive control power electronics, a special sphere decoder is, therefore, proposed in this article. The second subproblem consists of all those control goals that depend nonlinearly on the system inputs and is solved by an exhaustive search. The effectiveness of the proposed method is validated via numerical simulations at different scenarios on a three-level neutral-point-clamped permanent magnet synchronous generator wind turbine system and compared to other long-horizon model-predictive control methods.
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ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2021.3060694