Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/10252
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dc.coverage.spatialPerformance enhancement of induction motor drivesen_US
dc.date.accessioned2013-07-31T12:12:14Z-
dc.date.available2013-07-31T12:12:14Z-
dc.date.issued2013-07-31-
dc.identifier.urihttp://hdl.handle.net/10603/10252-
dc.description.abstractInduction motor is a major work horse in the modern industry. In the present work, an attempt is made for performance enhancement of induction motor using soft computing techniques for tailor made applications such as tyre manufacturing, steel mills, textile etc. Thus, the main contributions of the present investigation include; Formulation of a Genetic Algorithm (GA) based design methodology for optimizing the energy efficiency of the induction motor for a given loading pattern; Development of Extended Kalman Filter (EKF) based Real Time Recurrent Neural Network (RTRN) for robust performance of induction motor by simultaneously estimating rotor resistance and speed; Development of an ADALINE Artificial Neural Network (ANN) based switching scheme for torque ripple minimization of induction motor. Chapter 1 deals with the need for the present work, organization of the thesis along with the related literature survey. Mathematical modeling of induction motor is presented in Chapter 2. GA based induction motor design for performance enhancement is dealt in chapter 3. Chapter 4 highlights the robust parameter estimation of induction motor using EKF tuned RTRN. The torque ripple minimization scheme applied to Direct Torque Controlled induction motor drive using ADALINE ANN is presented in Chapter 5. The summary and conclusions are presented in Chapter 6. The major findings are; Energy efficiency of induction machines used for tailor made applications can be improved if the machine is exclusively designed for the given loading pattern using GA for optimizing the parameters; An ADALINE ANN based DTC strategy can be adapted for reducing the torque pulsations present in induction machines used for applications in wind farms; All these proposed methods lead to performance enhancement of induction motor drives. Thus, the proposed methodologies are viable solutions for performance enhancement of three phase induction motor for tailor made applications like steel mills, paper industry and tyre manufacturing unit. newlineen_US
dc.format.extentxvi, 101en_US
dc.languageEnglishen_US
dc.relation73en_US
dc.rightsuniversityen_US
dc.titleStudies on the performance enhancement of induction motor drives using soft computing techniquesen_US
dc.title.alternativeen_US
dc.creator.researcherGeetha Ramadasen_US
dc.subject.keywordInduction motor, soft computing techniques, genetic algorithm, extended kalman filter, Adaline Artificial Neural Networken_US
dc.description.noteNoneen_US
dc.contributor.guideThyagarajan.T.en_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Electrical and Electronics Engineeringen_US
dc.date.registered2, March 2011en_US
dc.date.completeden_US
dc.date.awardeden_US
dc.format.dimensions23.5 cm x 15 cmen_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File49.33 kBAdobe PDFView/Open
02_certificates.pdf829.35 kBAdobe PDFView/Open
03_abstract.pdf18.7 kBAdobe PDFView/Open
04_acknowledgement.pdf14.25 kBAdobe PDFView/Open
05_contents.pdf59.21 kBAdobe PDFView/Open
06_chapter 1.pdf63.99 kBAdobe PDFView/Open
07_chapter 2.pdf83.13 kBAdobe PDFView/Open
08_chapter 3.pdf117.1 kBAdobe PDFView/Open
09_chapter 4.pdf225.63 kBAdobe PDFView/Open
10_chapter 5.pdf470.1 kBAdobe PDFView/Open
11_chapter 6.pdf19.72 kBAdobe PDFView/Open
12_references.pdf39.94 kBAdobe PDFView/Open
13_publications.pdf17.36 kBAdobe PDFView/Open
14_vitae.pdf11.83 kBAdobe PDFView/Open


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