Cover
Vol. 13 No. 1 (2017)

Published: July 31, 2017

Pages: 67-72

Original Article

Hover Control for Helicopter Using Neural Network-Based Model Reference Adaptive Controller

Abdul-Basset A. Al-Hussein 1
1Electrical Engineering Department Basrah University Basrah, Iraq
History
  • Received: May 31, 2017
  • Available Online: July 31, 2017
DOI

https://doi.org/10.37917/ijeee.13.1.9

Abstract

Unmanned aerial vehicles (UAV), have enormous important application in many fields. Quanser three degree of freedom (3-DOF) helicopter is a benchmark laboratory model for testing and validating the validity of various flight control algorithms. The elevation control of a 3-DOF helicopter is a complex task due to system nonlinearity, uncertainty and strong coupling dynamical model. In this paper, an RBF neural network model reference adaptive controller has been used, employing the grate approximation capability of the neural network to match the unknown and nonlinearity in order to build a strong MRAC adaptive control algorithm. The control law and stable neural network updating law are determined using Lyapunov theory.

Keywords

References

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