---
_id: '10597'
abstract:
- lang: eng
  text: In comparison to classical control approaches in the field of electrical drives
    like the field-oriented control (FOC), model predictive control (MPC) approaches
    are able to provide a higher control performance. This refers to shorter settling
    times, lower overshoots, and a better decoupling of control variables in case
    of multi-variable controls. However, this can only be achieved if the used prediction
    model covers the actual behavior of the plant sufficiently well. In case of model
    deviations, the performance utilizing MPC remains below its potential. This results
    in effects like increased current ripple or steady state setpoint deviations.
    In order to achieve a high control performance, it is therefore necessary to adapt
    the model to the real plant behavior. When using an online system identification,
    a less accurate model is sufficient for commissioning of the drive system. In
    this paper, the combination of a finite-control-set MPC (FCS-MPC) with a system
    identification is proposed. The method does not require high-frequency signal
    injection, but uses the measured values already required for the FCS-MPC. An evaluation
    of the least squares-based identification on a laboratory test bench showed that
    the model accuracy and thus the control performance could be improved by an online
    update of the prediction models.
author:
- first_name: Soren
  full_name: Hanke, Soren
  last_name: Hanke
- first_name: Sebastian
  full_name: Peitz, Sebastian
  id: '47427'
  last_name: Peitz
  orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Oliver
  full_name: Wallscheid, Oliver
  last_name: Wallscheid
- first_name: Joachim
  full_name: Böcker, Joachim
  last_name: Böcker
- first_name: Michael
  full_name: Dellnitz, Michael
  last_name: Dellnitz
citation:
  ama: 'Hanke S, Peitz S, Wallscheid O, Böcker J, Dellnitz M. Finite-Control-Set Model
    Predictive Control for a Permanent Magnet Synchronous Motor Application with Online
    Least Squares System Identification. In: <i>2019 IEEE International Symposium
    on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)</i>.
    ; 2019. doi:<a href="https://doi.org/10.1109/precede.2019.8753313">10.1109/precede.2019.8753313</a>'
  apa: Hanke, S., Peitz, S., Wallscheid, O., Böcker, J., &#38; Dellnitz, M. (2019).
    Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous
    Motor Application with Online Least Squares System Identification. In <i>2019
    IEEE International Symposium on Predictive Control of Electrical Drives and Power
    Electronics (PRECEDE)</i>. <a href="https://doi.org/10.1109/precede.2019.8753313">https://doi.org/10.1109/precede.2019.8753313</a>
  bibtex: '@inproceedings{Hanke_Peitz_Wallscheid_Böcker_Dellnitz_2019, title={Finite-Control-Set
    Model Predictive Control for a Permanent Magnet Synchronous Motor Application
    with Online Least Squares System Identification}, DOI={<a href="https://doi.org/10.1109/precede.2019.8753313">10.1109/precede.2019.8753313</a>},
    booktitle={2019 IEEE International Symposium on Predictive Control of Electrical
    Drives and Power Electronics (PRECEDE)}, author={Hanke, Soren and Peitz, Sebastian
    and Wallscheid, Oliver and Böcker, Joachim and Dellnitz, Michael}, year={2019}
    }'
  chicago: Hanke, Soren, Sebastian Peitz, Oliver Wallscheid, Joachim Böcker, and Michael
    Dellnitz. “Finite-Control-Set Model Predictive Control for a Permanent Magnet
    Synchronous Motor Application with Online Least Squares System Identification.”
    In <i>2019 IEEE International Symposium on Predictive Control of Electrical Drives
    and Power Electronics (PRECEDE)</i>, 2019. <a href="https://doi.org/10.1109/precede.2019.8753313">https://doi.org/10.1109/precede.2019.8753313</a>.
  ieee: S. Hanke, S. Peitz, O. Wallscheid, J. Böcker, and M. Dellnitz, “Finite-Control-Set
    Model Predictive Control for a Permanent Magnet Synchronous Motor Application
    with Online Least Squares System Identification,” in <i>2019 IEEE International
    Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)</i>,
    2019.
  mla: Hanke, Soren, et al. “Finite-Control-Set Model Predictive Control for a Permanent
    Magnet Synchronous Motor Application with Online Least Squares System Identification.”
    <i>2019 IEEE International Symposium on Predictive Control of Electrical Drives
    and Power Electronics (PRECEDE)</i>, 2019, doi:<a href="https://doi.org/10.1109/precede.2019.8753313">10.1109/precede.2019.8753313</a>.
  short: 'S. Hanke, S. Peitz, O. Wallscheid, J. Böcker, M. Dellnitz, in: 2019 IEEE
    International Symposium on Predictive Control of Electrical Drives and Power Electronics
    (PRECEDE), 2019.'
date_created: 2019-07-10T08:15:23Z
date_updated: 2022-01-06T06:50:46Z
department:
- _id: '101'
doi: 10.1109/precede.2019.8753313
language:
- iso: eng
publication: 2019 IEEE International Symposium on Predictive Control of Electrical
  Drives and Power Electronics (PRECEDE)
publication_identifier:
  isbn:
  - '9781538694145'
publication_status: published
status: public
title: Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous
  Motor Application with Online Least Squares System Identification
type: conference
user_id: '47427'
year: '2019'
...