The Application of Artificial Intelligence Technology in Electrical Automation Control

Article Preview

Abstract:

Computer technology has become the world's most popular information technology, computer programming software technology continues to progress, leading people to the level of economic life. The human brain is the most advanced machines, all computer programming is to emulate human computer, the computer program to imitate the human brain as the main purpose to achieve our automation development. For electrical automation of the whole control process, it is through automation equipment to complete the entire process of production, distribution, etc. Thus to a large extent, reducing the cost and working efficiency are also increased accordingly. With the development of information technology, it constantly have new technology into engineering, and the transition phase, the automatic control technology put forward new challenges, promoting the theory of intelligence in the application of control technology, in order to solve the problem with traditional methods.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1049-1052

Citation:

Online since:

February 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Vas P. Artificial-intelligence-based electrical machines and drives: application of fuzzy, neural, fuzzy-neural, and genetic-algorithm-based techniques[M]. Oxford University Press, (1999).

Google Scholar

[2] Ramchurn S D, Vytelingum P, Rogers A, et al. Putting the'smarts' into the smart grid: a grand challenge for artificial intelligence[J]. Communications of the ACM, 2012, 55(4): 86-97.

DOI: 10.1145/2133806.2133825

Google Scholar

[3] Gadoue S M, Giaouris D, Finch J W. Artificial intelligence-based speed control of DTC induction motor drives—A comparative study[J]. Electric Power Systems Research, 2009, 79(1): 210-219.

DOI: 10.1016/j.epsr.2008.05.024

Google Scholar

[4] Ramos C, Augusto J C, Shapiro D. Ambient intelligence—The next step for artificial intelligence[J]. Intelligent Systems, IEEE, 2008, 23(2): 15-18.

DOI: 10.1109/mis.2008.19

Google Scholar

[5] Mellit A, Kalogirou S A, Hontoria L, et al. Artificial intelligence techniques for sizing photovoltaic systems: A review[J]. Renewable and Sustainable Energy Reviews, 2009, 13(2): 406-419.

DOI: 10.1016/j.rser.2008.01.006

Google Scholar