Fault tolerant speed regulation of Induction Motor using Artifical Neural Network

Kamran Zeb; Farhana; C. A. Mehmood; B. Khan; S. M. Ali; Ayesha; A. M. Jadoon; Waqar Uddin

doi:10.1109/ICET.2015.7389221

Fault tolerant speed regulation of Induction Motor using Artifical Neural Network

Kamran Zeb, Farhana, C. A. Mehmood, B. Khan, S. M. Ali, Ayesha, A. M. Jadoon, Waqar Uddin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

This paper successfully develops and investigates the implementation of Artificial Neural Network (ANN) based robust speed control strategy for Indirect Vector Control (IVC) three phase Induction Motor (IM) drive. The IM is modeled in terms of dq in synchronously rotating reference frame for IVC in Matlab/Simulink. The main purpose of the proposed design is to accomplish robustness for load disturbances, speed variation, parameter uncertainties, and electrical faults. The performance of aforesaid control technique is compared with that of conventional tuned PI control scheme. Simulation results of the ANN guarantee effectiveness and robustness regarding overshoot, undershoot, rise time, fall time and chattering for different operating condition in comparison to traditional PI control scheme.

Original language	English
Title of host publication	Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509004362
DOIs	https://doi.org/10.1109/ICET.2015.7389221
State	Published - 20 Jan 2016
Externally published	Yes

Publication series

Name	Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Artifical Neural Network (ANN)
Electrical Faults
Indirect Vector Control (IVC)
Induction Motor (IM)
PI Control
Rotor
Speed Variation
Stator

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Energy Engineering and Power Technology
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICET.2015.7389221

Cite this

Zeb, K., Farhana, Mehmood, C. A., Khan, B., Ali, S. M., Ayesha, Jadoon, A. M., & Uddin, W. (2016). Fault tolerant speed regulation of Induction Motor using Artifical Neural Network. In Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015 Article 7389221 (Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICET.2015.7389221

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title = "Fault tolerant speed regulation of Induction Motor using Artifical Neural Network",

abstract = "This paper successfully develops and investigates the implementation of Artificial Neural Network (ANN) based robust speed control strategy for Indirect Vector Control (IVC) three phase Induction Motor (IM) drive. The IM is modeled in terms of dq in synchronously rotating reference frame for IVC in Matlab/Simulink. The main purpose of the proposed design is to accomplish robustness for load disturbances, speed variation, parameter uncertainties, and electrical faults. The performance of aforesaid control technique is compared with that of conventional tuned PI control scheme. Simulation results of the ANN guarantee effectiveness and robustness regarding overshoot, undershoot, rise time, fall time and chattering for different operating condition in comparison to traditional PI control scheme.",

keywords = "Artifical Neural Network (ANN), Electrical Faults, Indirect Vector Control (IVC), Induction Motor (IM), PI Control, Rotor, Speed Variation, Stator",

author = "Kamran Zeb and Farhana and Mehmood, {C. A.} and B. Khan and Ali, {S. M.} and Ayesha and Jadoon, {A. M.} and Waqar Uddin",

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year = "2016",

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doi = "10.1109/ICET.2015.7389221",

language = "English",

series = "Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015",

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Zeb, K, Farhana, Mehmood, CA, Khan, B, Ali, SM, Ayesha, Jadoon, AM & Uddin, W 2016, Fault tolerant speed regulation of Induction Motor using Artifical Neural Network. in Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015., 7389221, Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICET.2015.7389221

Fault tolerant speed regulation of Induction Motor using Artifical Neural Network. / Zeb, Kamran; Farhana; Mehmood, C. A. et al.
Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015. Institute of Electrical and Electronics Engineers Inc., 2016. 7389221 (Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fault tolerant speed regulation of Induction Motor using Artifical Neural Network

AU - Zeb, Kamran

AU - Farhana,

AU - Mehmood, C. A.

AU - Khan, B.

AU - Ali, S. M.

AU - Ayesha,

AU - Jadoon, A. M.

AU - Uddin, Waqar

PY - 2016/1/20

Y1 - 2016/1/20

N2 - This paper successfully develops and investigates the implementation of Artificial Neural Network (ANN) based robust speed control strategy for Indirect Vector Control (IVC) three phase Induction Motor (IM) drive. The IM is modeled in terms of dq in synchronously rotating reference frame for IVC in Matlab/Simulink. The main purpose of the proposed design is to accomplish robustness for load disturbances, speed variation, parameter uncertainties, and electrical faults. The performance of aforesaid control technique is compared with that of conventional tuned PI control scheme. Simulation results of the ANN guarantee effectiveness and robustness regarding overshoot, undershoot, rise time, fall time and chattering for different operating condition in comparison to traditional PI control scheme.

AB - This paper successfully develops and investigates the implementation of Artificial Neural Network (ANN) based robust speed control strategy for Indirect Vector Control (IVC) three phase Induction Motor (IM) drive. The IM is modeled in terms of dq in synchronously rotating reference frame for IVC in Matlab/Simulink. The main purpose of the proposed design is to accomplish robustness for load disturbances, speed variation, parameter uncertainties, and electrical faults. The performance of aforesaid control technique is compared with that of conventional tuned PI control scheme. Simulation results of the ANN guarantee effectiveness and robustness regarding overshoot, undershoot, rise time, fall time and chattering for different operating condition in comparison to traditional PI control scheme.

KW - Artifical Neural Network (ANN)

KW - Electrical Faults

KW - Indirect Vector Control (IVC)

KW - Induction Motor (IM)

KW - PI Control

KW - Rotor

KW - Speed Variation

KW - Stator

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BT - Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Zeb K, Farhana, Mehmood CA, Khan B, Ali SM, Ayesha et al. Fault tolerant speed regulation of Induction Motor using Artifical Neural Network. In Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015. Institute of Electrical and Electronics Engineers Inc. 2016. 7389221. (Proceedings of 2015 International Conference on Emerging Technologies, ICET 2015). doi: 10.1109/ICET.2015.7389221

Fault tolerant speed regulation of Induction Motor using Artifical Neural Network

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this