<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents the results of simulation research of an off-line-trained, feedforward neural-network-based state estimator. The investigated system is the mechanical part of an electrical drive characterised by elastic coupling with a working machine, modelled as a dual-mass system. The aim of the research was to find a set of neural network structures giving useful and repeatable results of the estimation. The mechanical resonance frequency of the system has been adopted at the level of 9.3-10.3 Hz. The selected state variables of the mechanical system are load, speed and stiffness torque of the shaft.</p></abstract>

This paper presents the results of simulation research of an off-line-trained, feedforward neural-network-based state estimator. The investigated system is the mechanical part of an electrical drive characterised by elastic coupling with a working machine, modelled as a dual-mass system. The aim of the research was to find a set of neural network structures giving useful and repeatable results of the estimation. The mechanical resonance frequency of the system has been adopted at the level of 9.3-10.3 Hz. The selected state variables of the mechanical system are load, speed and stiffness torque of the shaft.

Neural State Estimator for Complex Mechanical Part of Electrical Drive: Neural Network Size and Performance of State Estimation

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

This paper presents the results of simulation research of an off-line-trained, feedforward neural-network-based state estimator. The investigated system is the...

Neural State Estimator for Complex Mechanical Part of Electrical Drive: Neural Network Size and Performance of State Estimation

Article Category: Special Section on Sensorless Drives

Online veröffentlicht: 17. Nov. 2018

Seitenbereich: 205 - 216

Eingereicht: 07. Juni 2018

Akzeptiert: 30. Sept. 2018

DOI: https://doi.org/10.2478/pead-2018-0017

Schlüsselwörter
two-mass drive, neural network, simulation studies, non-linear state estimation

© 2018 Dominik Łuczak, Adrian Wójcik, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Neural State Estimator for Complex Mechanical Part of Electrical Drive: Neural Network Size and Performance of State Estimation

Article Category: Special Section on Sensorless Drives

Online veröffentlicht: 17. Nov. 2018

Seitenbereich: 205 - 216

Eingereicht: 07. Juni 2018

Akzeptiert: 30. Sept. 2018

DOI: https://doi.org/10.2478/pead-2018-0017

Schlüsselwörtertwo-mass drive, neural network, simulation studies, non-linear state estimation

© 2018 Dominik Łuczak, Adrian Wójcik, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
two-mass drive, neural network, simulation studies, non-linear state estimation