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Journal of Advanced Transportation
Volume 2018, Article ID 3823201, 18 pages
Research Article

Neural Network Control System of UAV Altitude Dynamics and Its Comparison with the PID Control System

Department of Electrical Engineering, Universitas Indonesia, Kampus Baru UI, Depok 16424, Indonesia

Correspondence should be addressed to Benyamin Kusumoputro;

Received 5 May 2017; Revised 25 July 2017; Accepted 16 August 2017; Published 22 January 2018

Academic Editor: Cheng S. Chin

Copyright © 2018 Jemie Muliadi and Benyamin Kusumoputro. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This article proposes a comparative method to assess the performance of artificial neural network’s direct inverse control (DIC-ANN) with the PID control system. The comparison served as an analysis tool to assess the advantages of DIC-ANN over conventional control method for a UAV attitude controller. The development of ANN method for UAV control purposes arises due to the limitations of the conventional control method, which is the mathematical based model, involving complex expression, and most of them are difficult to be solved directly into analytic solution. Although the linearization simplified the solving process for such mathematical based model, omitting the nonlinear and the coupling terms is unsuitable for the dynamics of the multirotor vehicle. Thus, the DIC-ANN perform learning mechanism to overcome the limitation of PID tuning. Therefore, the proposed comparative method is developed to obtain conclusive results of DIC-ANN advantages over the linear method in UAV attitude control. Better achievement in the altitude dynamics was attained by the DIC-ANN compared to PID control method.