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Long-horizon direct model predictive control with active balancing of the neutral point potential

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Details

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)
PublisherIEEE
Pages89 - 94
Number of pages6
ISBN (Electronic)978-1-5386-0507-3
DOIs
Publication statusPublished - Sep 2017
Publication typeA4 Article in a conference publication
EventIEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics -
Duration: 1 Jan 1900 → …

Conference

ConferenceIEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics
Period1/01/00 → …

Abstract

In this paper we present modifications to the sphere decoder initially introduced in [1] to include the control of the neutral point (NP) potential of a three-level neutral point clamped (NPC) inverter. By linearizing the system model, the nonlinearities introduced by the dynamics of the NP potential are discarded. As a result, the optimization problem underlying direct model predictive control (MPC) can be formulated as an integer least-squares (ILS) one, and solved in a computationally efficient manner with a refined sphere decoding algorithm. As shown, thanks to the utilization of long prediction horizons, the system performance can be significantly improved. This is demonstrated with a variable speed drive consisting of a three-level NPC inverter and a medium-voltage induction machine.

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