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

Jemie Muliadi, Benyamin Kusumo Putro

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number3823201
JournalJournal of Advanced Transportation
Volume2018
DOIs
Publication statusPublished - 1 Jan 2018

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