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Title: Certain control approaches for the improvement in the performances of networked dc motor control with network challenges
Researcher: Sharmila B
Guide(s): Devarajan N
Keywords: Electrical engineering
Network challenges
Networked dc motor control
Upload Date: 28-Feb-2014
University: Anna University
Completed Date: 01/02/2013
Abstract: Use of networks in closed loop control system for remote control and newlineautomation has many advantages. Due to the network induced delay, missing newlineof data and disturbances in the networked control systems, the adverse effect newlinesuch as performance degradation and destabilization occur in the system. This newlineis a major concern in the networked control systems design. In this research certain approaches for the speed control of a DC newlinemotor is developed in a networked environment. The control strategy is to newlinestabilize and track the speed of the DC motor when the network induced delay newlineand packet losses occurs in the transport medium of the network data. A newlinenetworked control model of the DC motor is established. The PID control newlinealgorithm has been widely applied in field of industries to solve the network newlinechallenges because of its simple technology and good adaptability. However, newlinePID control algorithm faces difficulty in parameters tuning with the newlinechallenges in the network. Thus in order to overcome the inherence, the fuzzy newlinelogic modulator is first proposed to combine with PID controller to establish the control system. The fuzzy modulated PID controller integrates the advantages of PID newlinewith those of fuzzy logic control. Then a residual compensation approach newlinebased on intelligent controllers as artificial neural network NARMA-L2, an newlineapproximate model of nonlinear auto regressive moving average (NARMA) newlinemodel and fuzzy logic controller are employed to represent the input-output newlinebehavior of the motor and to provide the expected control input which newlineenhances the control accuracy of the system. For further improvement of the newlinecontrol performance, the combinations of neural and fuzzy as adaptive neurofuzzy newlinecontroller and the particle swarm optimization algorithm for PID controller as PID-PSO technique are employed to optimize the control newlinesystem. The effectiveness of the proposed controllers for networked DC newlinemotor system is synthesized by simulation. newline
Pagination: xxii, 160p.
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File42.82 kBAdobe PDFView/Open
02_certificate.pdf31.51 kBAdobe PDFView/Open
03_abstract.pdf87.91 kBAdobe PDFView/Open
04_acknowledgements.pdf60.27 kBAdobe PDFView/Open
05_contents.pdf885.79 kBAdobe PDFView/Open
06_chapter1.pdf403.13 kBAdobe PDFView/Open
07_chapter2.pdf1.93 MBAdobe PDFView/Open
08_chapter3.pdf4.93 MBAdobe PDFView/Open
09_chapter4.pdf7.78 MBAdobe PDFView/Open
10_chapter5.pdf9.07 MBAdobe PDFView/Open
11_chapter6.pdf4.8 MBAdobe PDFView/Open
12_chapter7.pdf145.1 kBAdobe PDFView/Open
13_references.pdf605.96 kBAdobe PDFView/Open
14_publications.pdf83.12 kBAdobe PDFView/Open
15_vitae.pdf39.32 kBAdobe PDFView/Open

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