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Title: Model reduction and control of linear discrete time control systems thesis
Researcher: Kavitha, M
Guide(s): Sundarapandian, V
Keywords: Mathematics
Model reduction
Upload Date: 20-Feb-2014
University: Vel Tech Dr. R R and Dr. S R Technical University
Completed Date: 2013
Abstract: Deriving reduced-order models for large-scale linear systems has been an active area of research in the control systems literature. Mathematical modelling and scientific computing are active areas of research in the control systems literature. In the analysis and design of algorithms for complex systems, it is often necessary to derive low order models simplifying high order system models. The use of a reduced order model makes it easier to implement analysis, simulations and control system designs. Also, there is a great demand from the industry to use low order models rather than high order models for physical or industrial systems because it is easy to work with low order models and design controllers, observers, etc. Some important reasons for using reduced order models of large scale linear systems are: 1) To have a better understanding of the large scale linear system. 2) To reduce the computational complexity of the system. newline3) To reduce the hardware complexity. 4) To make feasible controller and observer designs The methods available in the literature for reduced order model reduction for continuoustime and discrete-time linear control systems can be broadly classified into two areas: A) Classical control methods using the transfer-functions of the linear systems B) Modern control methods using the state-space models of the linear systems This dissertation is a modern control study, which derives new results for the model reduction of large-scale discrete-time control systems using the state-space models of the newlinesystems. There are many advantages of using modern control theory for linear control systems because the state space analysis is applicable to any types of linear control systems. The state space analysis can be performed with initial conditions and the variables used to represent the system can be any variables in the system. Using the modern control analysis, the internal states of the system at any time instant can be predicted.
Pagination: ix, 101p.
Appears in Departments:School of Science and Humanities

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01_title.pdfAttached File44.69 kBAdobe PDFView/Open
02_certificate.pdf199.4 kBAdobe PDFView/Open
03_abstract.pdf19.61 kBAdobe PDFView/Open
04_list of samples.pdf19.13 kBAdobe PDFView/Open
05_acknowledgements.pdf28.72 kBAdobe PDFView/Open
06_contents.pdf24.6 kBAdobe PDFView/Open
07_chapter 1.pdf32.4 kBAdobe PDFView/Open
08_chapter 2.pdf53.83 kBAdobe PDFView/Open
09_chapter 3.pdf125.68 kBAdobe PDFView/Open
10_chapter 4.pdf58.63 kBAdobe PDFView/Open
11_chapter 5.pdf95.26 kBAdobe PDFView/Open
12_chapter 6.pdf83.46 kBAdobe PDFView/Open
13_chapter 7.pdf123.11 kBAdobe PDFView/Open
14_chapter 8.pdf168.12 kBAdobe PDFView/Open
15_chapter 9.pdf147.65 kBAdobe PDFView/Open
16_chapter 10.pdf20.04 kBAdobe PDFView/Open
17_refernces.pdf62.91 kBAdobe PDFView/Open
18_publications.pdf38.26 kBAdobe PDFView/Open

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