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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151917
Doc. No : ET23709
Main Entry : Yamilka Isabel Bعez Rivera
Title Proper : Improved Gray-Box Modeling of Electric Drives using Neural Networks
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Electric drives are used in many industrial and commercial applications. Highperformance control of electric drives requires the accurate modeling of the motor andmechanical load. In many industrial applications, it is desirable that the electric drive hasthe capability of self-tuning controller parameters to be able to drive different mechanicalloads. One way to achieve this flexibility is by direct identification of the drive andmechanical load. Modeling and identification of Electric drive coupled to a load can be achallenging task. This research investigates the use of gray box models to identifyelectric drive systems connected to an unknown load.In the proposed model, the electrical subsystem of the machine is modeled usingphysical principles while the mechanical subsystem is modeled using a black box modelbased on neural networks. A two-stage identification approach that separates electricalsubsystem parameter estimation from mechanical subsystem identification is presented.At each stage the parameters are estimated.............-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46963.pdf
Title and statement of responsibility and : Improved Gray-Box Modeling of Electric Drives using Neural Networks [Thesis]
 
 
 
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