A Direct Model Predictive Control Strategy with Optimized Sampling Interval

Qifan Yang, Petros Karamanakos, Tobias Geyer, Ralph Kennel

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

In this paper we present a direct model predictive control (MPC) scheme with time-varying sampling intervals. These sampling intervals are computed based on modulation (half-)cycles, which are obtained offline and stored in a look-up table. By utilizing the optimized modulation (half-)cycles and combining control and modulation in one computational stage, the proposed direct MPC scheme achieves lower current total harmonic distortion (THD) than conventional linear controllers with a dedicated modulator, and fast transient responses that characterize direct control methods. The effectiveness of the proposed control scheme is verified on a variable speed drive system consisting of a two-level voltage source inverter and an induction machine.

Original languageEnglish
Title of host publication6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
PublisherIEEE
Pages268-274
Number of pages7
ISBN (Electronic)9781665425575
DOIs
Publication statusPublished - 2022
Publication typeA4 Article in a conference publication
EventIEEE International Conference on Predictive Control of Electrical Drives and Power Electronics - Jinan, China
Duration: 20 Nov 202122 Nov 2021

Publication series

NameIEEE International Conference on Predictive Control of Electrical Drives and Power Electronics

Conference

ConferenceIEEE International Conference on Predictive Control of Electrical Drives and Power Electronics
Country/TerritoryChina
CityJinan
Period20/11/2122/11/21

Keywords

  • AC drives
  • direct control
  • model predictive control (MPC)
  • optimized modulation cycles

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Control and Systems Engineering

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