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Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives

Induction motor drives are commonly applicable in various industrial applications, such as traction system, electric vehicle and home appliances. This high performance drive require robust controller to obtain satisfactory performance in terms of speed demand change, load disturbance, inertia variat...

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Main Author: Farah,, Nabil Salem Yahya
Format: Thesis
Language:English
English
Published: 2019
Subjects:
T Technology (General)
TJ Mechanical engineering and machinery
Online Access:http://eprints.utem.edu.my/id/eprint/24692/1/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf
http://eprints.utem.edu.my/id/eprint/24692/2/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf
http://eprints.utem.edu.my/id/eprint/24692/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=116934
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spelling my.utem.eprints.246922021-10-05T10:15:43Z http://eprints.utem.edu.my/id/eprint/24692/ Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives Farah,, Nabil Salem Yahya T Technology (General) TJ Mechanical engineering and machinery Induction motor drives are commonly applicable in various industrial applications, such as traction system, electric vehicle and home appliances. This high performance drive require robust controller to obtain satisfactory performance in terms of speed demand change, load disturbance, inertia variation and non-linearity. Fuzzy Logic Control (FLC) is suitable for controller design especially when the system is difficult to be modelled mathematically due to its complexity, nonlinearity and imprecision. However, FLC with fixed parameters may experience degradation when the system operates away from the design point, and encounters parameter variation or load disturbance. The purpose of this project is to design and implement Self-Tuning Fuzzy Logic Controller (ST-FLC) for Induction Motor (IM)drives. The proposed self-tuning mechanism is able to adjust the output scaling factor of the output controller for main FLC. This process enhances the accuracy of the crisp output. This research begins by designing Indirect Field Oriented Control (IFOC) method fed by Hysteresis Current Controller (HCC) induction motor drive system. The FLC with fixed parameters for the speed controller comprises 9-rules are tuned to achieve best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulations are executed by using Simulink and fuzzy tools in MATLAB software. The effectiveness of the proposed controller is determined by conducting a comparative analysis between FLC with fixed parameters and ST-FLC over a wide range of operating conditions, either in forward and reverse operations, load disturbance or inertia variations. Finally, experimental investigation is carried out to validate the simulation results by the aid of digital signal controller board dSPACE DS1104 with the induction motor drives system. Based on the results, ST-FLC has shown superior performance in transient and steady state conditions in term of various performance measures such as overshoot, rise time, settling time and recovery time over wide speed range operation. In comparison to fixed parameter FLC, the proposed ST-FLC reduced the settling time by 40.5%, rise time by 47.3% and speed drop by 19.2%. The proposed self-tuning mechanism is relatively simpler and consumes less computational burden compared to other self-tuning methods. This is proved by measuring the computational burden of another Self-Tuning method which used fuzzy rules to tune the output scaling factor. The execution time of the proposed self-tuning found to be 0.5 x10−3 seconds compared to 1.2 x10−3 seconds for the other self-tuning. 2019 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/24692/1/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf text en http://eprints.utem.edu.my/id/eprint/24692/2/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf Farah,, Nabil Salem Yahya (2019) Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives. Masters thesis, Universiti Teknikal Malaysia Melaka. https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=116934
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
English
topic T Technology (General)
TJ Mechanical engineering and machinery
spellingShingle T Technology (General)
TJ Mechanical engineering and machinery
Farah,, Nabil Salem Yahya
Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives
description Induction motor drives are commonly applicable in various industrial applications, such as traction system, electric vehicle and home appliances. This high performance drive require robust controller to obtain satisfactory performance in terms of speed demand change, load disturbance, inertia variation and non-linearity. Fuzzy Logic Control (FLC) is suitable for controller design especially when the system is difficult to be modelled mathematically due to its complexity, nonlinearity and imprecision. However, FLC with fixed parameters may experience degradation when the system operates away from the design point, and encounters parameter variation or load disturbance. The purpose of this project is to design and implement Self-Tuning Fuzzy Logic Controller (ST-FLC) for Induction Motor (IM)drives. The proposed self-tuning mechanism is able to adjust the output scaling factor of the output controller for main FLC. This process enhances the accuracy of the crisp output. This research begins by designing Indirect Field Oriented Control (IFOC) method fed by Hysteresis Current Controller (HCC) induction motor drive system. The FLC with fixed parameters for the speed controller comprises 9-rules are tuned to achieve best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulations are executed by using Simulink and fuzzy tools in MATLAB software. The effectiveness of the proposed controller is determined by conducting a comparative analysis between FLC with fixed parameters and ST-FLC over a wide range of operating conditions, either in forward and reverse operations, load disturbance or inertia variations. Finally, experimental investigation is carried out to validate the simulation results by the aid of digital signal controller board dSPACE DS1104 with the induction motor drives system. Based on the results, ST-FLC has shown superior performance in transient and steady state conditions in term of various performance measures such as overshoot, rise time, settling time and recovery time over wide speed range operation. In comparison to fixed parameter FLC, the proposed ST-FLC reduced the settling time by 40.5%, rise time by 47.3% and speed drop by 19.2%. The proposed self-tuning mechanism is relatively simpler and consumes less computational burden compared to other self-tuning methods. This is proved by measuring the computational burden of another Self-Tuning method which used fuzzy rules to tune the output scaling factor. The execution time of the proposed self-tuning found to be 0.5 x10−3 seconds compared to 1.2 x10−3 seconds for the other self-tuning.
format Thesis
author Farah,, Nabil Salem Yahya
author_facet Farah,, Nabil Salem Yahya
author_sort Farah,, Nabil Salem Yahya
title Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives
title_short Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives
title_full Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives
title_fullStr Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives
title_full_unstemmed Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives
title_sort self-tuning fuzzy logic speed control of induction motor drives
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24692/1/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf
http://eprints.utem.edu.my/id/eprint/24692/2/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf
http://eprints.utem.edu.my/id/eprint/24692/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=116934
_version_ 1713203453710303232
score 13.211869

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