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Title: Linear system model reduction using Genetic algorithm
Researcher: Suganthi, J
Guide(s): Sivanandam, S N
Keywords: Genetic algorithm
Upload Date: 3-Nov-2014
University: Anna University
Completed Date: 01/07/2007
Abstract: newlineStability is an important property to be possessed by every system newlineSince most of the systems are non linear in nature the analysis about the newlinestability of a system can be acquired by employing suitable linearised models newlineThe stability analysis of linear time invariant systems given in the form of newlinecharacteristic equation can be performed using algebraic or graphical method newlineThe characteristic equation is one kind of time invariant model Even linear newlinemodels may need further simplification to enable feasible analysis Model newlinereduction technique is used for this purpose All model reduction techniques newlineaim to provide a lower order model that will mimic the characteristics of the newlinegiven higher order system Also the design of controllers and observers for newlinehigher order linear time invariant system involves large computational newlineburden which can be minimized with the help of suitable reduced order newlinemodels newline
Pagination: xxv, 274p.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File40.5 kBAdobe PDFView/Open
02_certificate.pdf5.65 kBAdobe PDFView/Open
03_abstract.pdf14.85 kBAdobe PDFView/Open
04_acknowledgement.pdf6.55 kBAdobe PDFView/Open
05_content.pdf48.76 kBAdobe PDFView/Open
06_chapter1.pdf112.2 kBAdobe PDFView/Open
07_chapter2.pdf231.2 kBAdobe PDFView/Open
08_chapter3.pdf120.76 kBAdobe PDFView/Open
09_chapter4.pdf223.68 kBAdobe PDFView/Open
10_chapter5.pdf193.44 kBAdobe PDFView/Open
11_chapter6.pdf390.85 kBAdobe PDFView/Open
12_chapter7.pdf35.59 kBAdobe PDFView/Open
13_appendix.pdf65.25 kBAdobe PDFView/Open
14_reference.pdf37.71 kBAdobe PDFView/Open
15_publication.pdf9.96 kBAdobe PDFView/Open
16_vitae.pdf6.47 kBAdobe PDFView/Open

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