Paper Info
Title
A Novel Speed Control for DC Motors: Sliding Mode Control, Fuzzy Inference System, Neural Networks and Genetic Algorithms
Abstract
DC motors have been leading the field of adjustable speed drives for a long time due to its excellent control characteristics. This paper addresses a novel speed control application for DC motors gathering the features of Sliding Mode Control (SMC), Fuzzy Inference System (FIS), Neural Networks (NNs) and Genetic Algorithms (GAs). The main goal about combining these techniques is to create a robust speed controller avoiding the main disadvantage of SMC, the chattering. The design of the controller is implemented on a FPGA (Field Programmable Gate Array) and the steps for carrying out the implementation are described in detail. Finally, the results show a comparison between three different schemes of the designed controller.
Year
DOI
Venue
2012
10.1109/MICAI.2012.32
MICAI (Special Sessions)
Keywords
Field
DocType
DC motors,angular velocity control,control engineering computing,control system synthesis,electric machine analysis computing,field programmable gate arrays,fuzzy reasoning,genetic algorithms,machine control,neural nets,robust control,variable speed drives,variable structure systems,DC motors,FIS,FPGA,GA,NN,SMC,adjustable speed drives,designed controller,field programmable gate array,fuzzy inference system,genetic algorithms,neural networks,robust speed controller,sliding mode control,DC motors,Sliding Mode Control,Fuzzy Inference System,Neural Networks,Genetic Algorithms,chattering,Field Programmable Gate Array
Control theory,Computer science,Control theory,DC motor,Robust control,Artificial neural network,Genetic algorithm,Sliding mode control,Electronic speed control,Machine control
Conference
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Paul Cepeda100.34
Pedro Ponce22418.14
Arturo Molina33515.78