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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2012 Vol.2(6): 882-885 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.258

Application of Neural Network on Flight Control

Mohammad Reza Khosravani
Abstract—Over the last three decades, adaptive control has evolved as a powerful methodology for designing feedback controller of nonlinear systems. Most of the studies assume that the system nonlinearities are known a prior, which is generally not applicable in the real world. To overcome this drawback, from twenty years ago, there has been a tremendous amount of activity in applying Neural Networks for adaptive control. With their powerful ability to approximate nonlinear functions, neuro-controllers can implement the expected objectives by canceling or learning the unknown nonlinearities of the system to be cancelled. Neural Networks are specially suitable for the adaptive flight control applications where system dynamics are dominated by the unknown nonlinearities.

Index Terms—Control, flight, neural network.

Mohammad Reza Khosravani is with the Mechanical Engineering postgraduate student at Universiti Teknologi Malaysia (e-mail: rkmohammad2@live.utm.my).


Cite:Mohammad Reza Khosravani, "Application of Neural Network on Flight Control," International Journal of Machine Learning and Computing vol.2, no. 6, pp. 2010-3700, 2012.

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