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: firstname.lastname@example.org).
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.