IoT integrated adaptive fault tolerant control for induction motor based critical load applications

The concept of Industry 4.0 is flexible monitoring, uninterrupted services, cost-effectiveness, and things connected to networks. Industrial drives with various sensing and controlling units are the key components of every industrial process. In electric drive, the current sensor and speed encoder a...

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Main Authors: Dattatraya Kalel, R. Raja Singh
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Engineering Science and Technology, an International Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S221509862300263X
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author Dattatraya Kalel
R. Raja Singh
author_facet Dattatraya Kalel
R. Raja Singh
author_sort Dattatraya Kalel
collection DOAJ
description The concept of Industry 4.0 is flexible monitoring, uninterrupted services, cost-effectiveness, and things connected to networks. Industrial drives with various sensing and controlling units are the key components of every industrial process. In electric drive, the current sensor and speed encoder are used for controlling the system. A fault in the sensing unit could interrupt the process, which causes production losses. In this paper, a fast and smooth switching control strategy is designed and deployed for induction motor drives (IMD) to enhance system reliability and provide uninterrupted services. Based on supervisory decisions, suitable control strategies such as field-oriented control, slip compensation, and scalar control are chosen as alternatives during sensor failure. The adaptive reconfigurable fault-tolerant control technique (ARFTC) is employed for IMD, which can mitigate the transient issues while transitioning between different controls. This ARFTC scheme involves the DC-type feature of the synchronous-frame voltage commands (Vds∗,Vqs∗) and the synchronization of the rotor angle between the different control strategies. Under sensor-fault conditions, ARFTC enables better performance on the drive. Furthermore, cost-effective IoT monitoring services are integrated into the system for analyzing the performance of the drive. The proposed ARFTC is deployed in real-time on the industrial drive VLT-302 using the dSPACE MicroLabBox controller and Alborg interfacing and protection card. The proposed adaptive scheme is experimentally evaluated with a 2.2 kW squirrel cage induction motor under various sensor fault conditions. The obtained results shows that the proposed ARFTC is constructive for enhancing the reliability of induction motor drives, especially in sensor failure situations.
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spelling doaj.art-3793e34c7fc04a17a71c6772dafa70282024-03-17T07:54:27ZengElsevierEngineering Science and Technology, an International Journal2215-09862024-03-0151101585IoT integrated adaptive fault tolerant control for induction motor based critical load applicationsDattatraya Kalel0R. Raja Singh1School of Electrical Engineering, Vellore Institute of Technology, Vellore 632 014, IndiaAutomotive Research Center, Vellore Institute of Technology, Vellore 632 014, India; Corresponding author.The concept of Industry 4.0 is flexible monitoring, uninterrupted services, cost-effectiveness, and things connected to networks. Industrial drives with various sensing and controlling units are the key components of every industrial process. In electric drive, the current sensor and speed encoder are used for controlling the system. A fault in the sensing unit could interrupt the process, which causes production losses. In this paper, a fast and smooth switching control strategy is designed and deployed for induction motor drives (IMD) to enhance system reliability and provide uninterrupted services. Based on supervisory decisions, suitable control strategies such as field-oriented control, slip compensation, and scalar control are chosen as alternatives during sensor failure. The adaptive reconfigurable fault-tolerant control technique (ARFTC) is employed for IMD, which can mitigate the transient issues while transitioning between different controls. This ARFTC scheme involves the DC-type feature of the synchronous-frame voltage commands (Vds∗,Vqs∗) and the synchronization of the rotor angle between the different control strategies. Under sensor-fault conditions, ARFTC enables better performance on the drive. Furthermore, cost-effective IoT monitoring services are integrated into the system for analyzing the performance of the drive. The proposed ARFTC is deployed in real-time on the industrial drive VLT-302 using the dSPACE MicroLabBox controller and Alborg interfacing and protection card. The proposed adaptive scheme is experimentally evaluated with a 2.2 kW squirrel cage induction motor under various sensor fault conditions. The obtained results shows that the proposed ARFTC is constructive for enhancing the reliability of induction motor drives, especially in sensor failure situations.http://www.sciencedirect.com/science/article/pii/S221509862300263XIoTVLT 302 drivesFault diagnosisFault-tolerant controlInduction motor
spellingShingle Dattatraya Kalel
R. Raja Singh
IoT integrated adaptive fault tolerant control for induction motor based critical load applications
Engineering Science and Technology, an International Journal
IoT
VLT 302 drives
Fault diagnosis
Fault-tolerant control
Induction motor
title IoT integrated adaptive fault tolerant control for induction motor based critical load applications
title_full IoT integrated adaptive fault tolerant control for induction motor based critical load applications
title_fullStr IoT integrated adaptive fault tolerant control for induction motor based critical load applications
title_full_unstemmed IoT integrated adaptive fault tolerant control for induction motor based critical load applications
title_short IoT integrated adaptive fault tolerant control for induction motor based critical load applications
title_sort iot integrated adaptive fault tolerant control for induction motor based critical load applications
topic IoT
VLT 302 drives
Fault diagnosis
Fault-tolerant control
Induction motor
url http://www.sciencedirect.com/science/article/pii/S221509862300263X
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