Detail publikace

Discrete-Time Modeling of PMSM for Parametric Estimation and Model Predictive Control Tasks

ZEZULA, L. BLAHA, P.

Originální název

Discrete-Time Modeling of PMSM for Parametric Estimation and Model Predictive Control Tasks

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper presents novel implicit and explicit discrete-time permanent magnet synchronous motor models. Both derived models solve the problem of numerical instability and poor precision of motor currents' discrete-time prototypes formed using the forward Euler method and preserve the tolerable complexity of resulting descriptions. Discrete-time models of currents are derived based on the linear time-varying systems approach, considering the electrical angular velocity time-varying parameter. Angular velocity and angle are discretized by using the linear multistep methods. The implicit variant of the model is dedicated to parametric estimation tasks, and the explicit variant is to model predictive control. The derived descriptions are validated within the simulation by comparing the original continuous-time model and Euler approximation with the explicit model. Furthermore, the prediction capabilities of the explicit model and Euler approximation are compared as well.

Klíčová slova

discrete-time systems, mathematical models, model checking, parameter estimation, permanent magnet motors, predictive control, predictive models, systems modeling

Autoři

ZEZULA, L.; BLAHA, P.

Vydáno

16. 11. 2023

Nakladatel

IEEE

ISBN

979-8-3503-3182-0

Kniha

IECON 2023: 49th Annual Conference of the IEEE Industrial Electronics Society

Strany počet

6

URL

https://ieeexplore.ieee.org/document/10312226

Plný text v Digitální knihovně

http://hdl.handle.net/11012/244305

BibTex

@inproceedings{BUT185380,
  author="Lukáš {Zezula} and Petr {Blaha}",
  title="Discrete-Time Modeling of PMSM for Parametric Estimation and Model Predictive Control Tasks",
  booktitle="IECON 2023: 49th Annual Conference of the IEEE Industrial Electronics Society",
  year="2023",
  pages="6",
  publisher="IEEE",
  doi="10.1109/IECON51785.2023.10312226",
  isbn="979-8-3503-3182-0",
  url="https://ieeexplore.ieee.org/document/10312226"
}

Dokumenty

IECON_IPMSM_discr.pdf