Noor Salam Al-Fallooji

Work place: Department of Electronic and Computer Engineering, School of Engineering, Design and Physical Science, Brunel University London, UK

E-mail: 1442218@alumni.brunel.ac.uk

Website:

Research Interests:

Biography

Noor Al-Fallooji was born in 1983. She received BSc Degree in Electrical Engineering from the University of Babylon in 2004, MSc in Advanced Electronic and Electrical Engineering from Brunel University London/ United Kingdom in 2016. Her research focuses on Artificial Intelligence and Power Distribution. She is currently an electrical engineer in the General Electricity Distribution Company in Iraq. Her main job is as a supervisor and executive engineer in many projects.

Author Articles
Helicopter Control Using Fuzzy Logic and Narma-L2 Techniques

By Noor Salam Al-Fallooji Maysam Abbod

DOI: https://doi.org/10.5815/ijisa.2020.05.01, Pub. Date: 8 Oct. 2020

Helicopter instability is one of the most limitations that should be addressed in a nonlinear application. Accordingly, researchers are invited to design a robust and reliable controller to obtain a stable system and enhance its overall performance. The present study focuses on the use of the intelligent system in controlling the pitch and yaw angles. This lead to controlling the elevation and the direction of the helicopter. Further to the application of the Linear Quadratic Regulator (LQR) controller, this research implemented the Proportional Integral Derivative (PID), Fuzzy Logic Control (FLC), and Artificial Neural Network (ANN). The results show that FLC achieved a good controllability for both angles, particularly for the pitch angle in comparison to the nonlinear auto regressive moving average (NARMA-L2). Moreover, NARMA-L2 requires further improvement by using, for example, the swarm optimization method to provide better controllability. The PID controller, on the other hand, had a greater capability in controlling the yaw angle in comparison to the other controllers implemented. Accordingly, it is suggested that the integration of PID and FLC may lead to more optimal outcomes.

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