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This book focuses on model predictive control (MPC) schemes for industrial power electronics. The emphasis is on three-phase ac–dc and dc–ac power conversion systems for high-power applications of 1 MVA and above. These systems are predominantly based on multilevel voltage source converters that operate at switching frequencies well below 1 kHz. The book mostly considers medium-voltage (MV), variable-speed drive systems and, to a lesser extent, MV grid-connected converters.




The proposed control techniques can also be applied to low-voltage power converters when operated at low pulse number, that is, at small ratios between the switching frequency and the fundamental frequency. For high-power converters, the pulse number typically ranges between 5 and 15. As a result, the concept of averaging, which is commonly applied to power electronic systems to conceal the switching aspect from the control problem, leads to performance deterioration.




In general, to achieve the highest possible performance for a high-power converter, averaging is to be avoided, and the traditionally used current control loop and modulator should be replaced by one single control entity. This book proposes and reviews control methods that fully exploit the performance potential of high-power converters, by ensuring fast control at very low switching frequencies and low harmonic distortions. To achieve this, the control and modulation problem is addressed in one computational stage. Long prediction horizons are required for the MPC controllers to achieve excellent steady-state performance.




The resulting optimization problem is computationally challenging, but can be solved in real time by branch-and-bound methods. Alternatively, the optimal switching sequence to be applied during steady-state operation—the so-called optimized pulse pattern (OPP)—can be precomputed offline and refined online to achieve fast closed-loop control. To this end, the research vision is to combine the benefits of deadbeat control methods (such as direct torque control) with the optimal steady-state performance of OPPs, by resolving the antagonism between the two. Three such MPC methods are presented in detail.




First and foremost, I would like to thank Georgios Papafotiou, who introduced me to the exciting field of power electronics, Stefan Schröder, who taught me the fundamentals of high power electronics, and Manfred Morari, who showed me how to achieve meaningful research results. I am deeply grateful to my wife Jan for her love and support, which allowed me to work during long nights, weekends, and holidays to finalize this book. I apologize to my children Luci and David for having spared little time for them. I thank my parents for being role models of diligence and scientific curiosity. Over the years, I had the privilege of collaborating with many outstanding control and power electronics researchers. I would like to particularly mention Daniel Quevedo, Toit Mouton, Stefan Schröder, Georgios Papafotiou, and Petros Karamanakos.




I would also like to thank Johann Kolar, José Rodríguez, and Ralph Kennel for their support and encouragement. I am very grateful to Andrew Paice, Jan-Henning Fabian, John Boys, Grant Covic, Udaya Madawala, and Keith Jones for facilitating and supporting my affiliation with the University of Auckland. The majority of the concepts and results in this book are due to this very productive 3.5 years, during which I had few obligations and the unique opportunity to exclusively focus on research.




At ABB, I have had the pleasure of working with many able colleagues on control-related topics that are part of this book. I am particularly grateful to Nikolaos Oikonomou, Wim van der Merwe, Peter Al Hokayem, Vedrana Spudic, Christian Stulz, Eduardo Rohr, Andrea Rüetschi, ´Thomas Burtscher, Christof Gutscher, Andrey Kalygin, Rick Kieferndorf, Silvia Mastellone, Helfried Peyrl, Jan Poland, Tobias Thurnherr, and Michail Vasiladiotis. A special word of gratitude is reserved for Gerald Scheuer for his steadfast support of and conviction in modern control methodologies. Many MSc and PhD students contributed through their thesis work to this book.




Among them, I would like to specifically thank James Scoltock, Baljit Riar, Thomas Burtscher, Aleksandar Paunovic, Georgios Darivianakis, Yashar Zeinaly, and Joël Vallone. It was a pleasure ´ to work with them, and I am grateful for their hard work, curiosity, and ideas.


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