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General Information
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 2013 Vol.3(1): 35-38 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.268

An Optimal Adaptive Flight Control System

Mojtaba Vahedi, Ali Akbarzadeh Kalat, and Mohammad Hadad Zarif
Abstract—In This paper, an optimal self tuning regulator (STR) structure is applied to a nonlinear flight system. In control structure, a modified GA algorithm for obtaining a suitable observer polynomial is proposed which optimizes the controller performance. The proposed method has two major advantages; first of all, it is independent of system degree or system complexity and secondly, in this method some of unknown STR method parameters such as observer polynomial are discarded. The designed controller is applied to a F-18 nonlinear model. Simulation results are presented which show that in the closed-loop system asymptotic trajectory control is accomplished. Also computer simulations are carried out for showing the performance of the designed controller against common STR controller.

Index Terms—Self tuning regulator, genetic algorithm, flight control.

M. Vahedi is with the Electrical and Computer Department, Islamic Azad University, Shahrood branch. Shahrood, Iran (e-mail: vahedi.mojtaba@yahoo.com).
A. Akbarzadeh Kalat and M. Hadad Zarif are with the Electrical and robotic Engineering Department, shahrood university of technology, Shahrood, Iran (e-mail: aliakkalat@yahoo.com; mhzarif@shahroodut.ac.ir).


Cite:Mojtaba Vahedi, Ali Akbarzadeh Kalat, and Mohammad Hadad Zarif, "An Optimal Adaptive Flight Control System," International Journal of Machine Learning and Computing vol. 3, no. 1, pp. 35-38, 2013.

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