Model predictive control in power electronics: Strategies to reduce the computational complexity

Model predictive control (MPC) is a control strategy that has been gaining more and more attention in the field of power electronics. However, in many cases the computational requirements of the derived MPC-based algorithms are difficult to meet, even with modern microprocessors that are immensely powerful and capable of executing complex instructions at a faster rate than ever before. To overcome this difficulty, three strategies that can significantly reduce the complexity of computationally demanding MPC schemes are presented in this paper. Three case studies are examined in order to verify the effectiveness of the proposed strategies. These include a move blocking strategy for a dc-dc boost converter and both an extrapolation strategy and an event-based horizon strategy for a dc-ac medium-voltage (MV) drive.

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