In his doctoral dissertation, Andrei Tregubov explored that medium-voltage power converters – which can be used in wind farms, industrial drives, and grid systems – can fully leverage the performance benefits of long-horizon model predictive control without excessive computational cost. By reformulating the control problem, the approach cuts complexity by over 99.9%, enabling real-time implementation while improving dynamic response and reducing harmonic distortion by up to 30%. These advances enable more stable and adaptable power systems, supporting the transition toward sustainable and efficient power electronic applications in critical infrastructure.
The doctoral dissertation of M. Sc. Andrei Tregubov in the field of electrical engineering titled Computationally Efficient Direct Model Predictive Control with Increased Robustness for Medium-Voltage Power Conversion Systems will be publicly examined at the Faculty of Information Technology and Communication Sciences at Tampere University on 19 December 2025.
The Opponent will be Professor Sergio Vazquez Perez from the University of Seville, Spain. The Custos will be Associate Professor Petros Karamanakos the Faculty of Information Technology and Communication Sciences, Tampere University.