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Alternative control methods for DC–DC converters: An application to a four‐level three‐cell DC–DC converter
Author(s) -
Patino Diego,
Bâja Mihai,
Riedinger Pierre,
Cormerais Hervé,
Buisson Jean,
Iung Claude
Publication year - 2010
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1651
Subject(s) - converters , control theory (sociology) , benchmark (surveying) , waveform , model predictive control , stability (learning theory) , computer science , control (management) , engineering , voltage , geodesy , artificial intelligence , machine learning , electrical engineering , geography
This paper proposes three synthesis methods for controlling power converters. The three control strategies yield state feedback control laws that are easy to implement. The first method is a stabilization approach, based on energetic principles and the notion of Lyapunov function. The second is an optimal control approach based on the minimum principle. The third is a neural predictive approach which uses model predictive control to track a given optimal stable limit cycle. This method allows a proper control of the waveform. Except for the predictive approach, system stability for the methods is guaranteed by construction. The four‐level three‐cell DC–DC converter is used as a benchmark to test these strategies. Simulation and experimental results show that the methods have a good performance even with load perturbations. Copyright © 2010 John Wiley & Sons, Ltd.