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Application of Computational Intelligence in Motor Modeling

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International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 35 - Number 12
Year of Publication: 2011
Authors:
Yousuf Ibrahim Khan
Shahriar Rahman
Debasis Baishnab
Mohammed Moaz
S.M. Musfequr Rahman
10.5120/4556-6443

Yousuf Ibrahim Khan, Shahriar Rahman, Debasis Baishnab, Mohammed Moaz and S.M.Musfequr Rahman. Article: Application of Computational Intelligence in Motor Modeling. International Journal of Computer Applications 35(12):43-50, December 2011. Full text available. BibTeX

@article{key:article,
	author = {Yousuf Ibrahim Khan and Shahriar Rahman and Debasis Baishnab and Mohammed Moaz and S.M.Musfequr Rahman},
	title = {Article: Application of Computational Intelligence in Motor Modeling},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {35},
	number = {12},
	pages = {43-50},
	month = {December},
	note = {Full text available}
}

Abstract

Modeling is very important in the field of science and engineering. Modeling gives us an abstract and mathematical description of a particular system and describes its behavior. Once we get the model of a system then we can work with that in various applications without using the original system repeatedly. Computational Intelligence method like Artificial Neural Network is very sophisticated tool for modeling and data fitting problems. Modeling of Electrical motors can also be done using ANN. The Neural network that will represent the model of the motor will be a useful tool for future use especially in digital control systems. The parallel structure of a neural network makes it potentially fast for the computation of certain tasks. The same feature makes a neural network well suited for implementation in VLSI technology. Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. In this paper only a motor model is presented along with some neural networks those will mimic the motor behavior acquiring data from the original motor output.

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