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Volume 10
Issue 7
10.3390/pr10071236
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Article

Data Driven Model Estimation for Aerial Vehicles: A Perspective Analysis

by
Syeda Kounpal Fatima
1,
Manzar Abbas
1,
Imran Mir
1,*,
Faiza Gul
2,
Suleman Mir
3,
Nasir Saeed
4,5,*,
Abdullah Alhumaidi Alotaibi
6,
Turke Althobaiti
5,7 and
Laith Abualigah
8,9
1
Department of Avionics Engineering, Air University, Aerospace and Aviation Campus Kamra, Islamabad 43600, Pakistan
2
Department of Electrical Engineering, Air University, Aerospace and Aviation Campus Kamra, Islamabad 43600, Pakistan
3
Electrical Department, Fast-National University of Computer & Emerging Sciences, Peshawar 25000, Pakistan
4
Department of Electrical Engineering, Northern Border University, Arar 73222, Saudi Arabia
5
Remote Sensing Unit, Northern Border University, Arar 73222, Saudi Arabia
6
Department of Science and Technology, College of Ranyah, Taif Univeristy, P.O. Box 11099, Taif 21944, Saudi Arabia
7
Department of Computer Science, Faculty of Science, Northern Border University, Arar 73222, Saudi Arabia
8
Faculty of Computer Sciences and Informatics, Amman Arab University, Amman 11953, Jordan
9
Faculty of Information Technology, Middle East University, Amman 11831, Jordan
*
Authors to whom correspondence should be addressed.
Processes 2022, 10(7), 1236; https://doi.org/10.3390/pr10071236
Submission received: 17 May 2022 / Revised: 8 June 2022 / Accepted: 9 June 2022 / Published: 21 June 2022
(This article belongs to the Special Issue Evolutionary Process for Engineering Optimization)
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Abstract

Unmanned Aerial Vehicles (UAVs) are important tool for various applications, including enhancing target detection accuracy in various surface-to-air and air-to-air missions. To ensure mission success of these UAVs, a robust control system is needed, which further requires well-characterized dynamic system model. This paper aims to present a consolidated framework for the estimation of an experimental UAV utilizing flight data. An elaborate estimation mechanism is proposed utilizing various model structures, such as Autoregressive Exogenous (ARX), Autoregressive Moving Average exogenous (ARMAX), Box Jenkin’s (BJ), Output Error (OE), and state-space and non-linear Autoregressive Exogenous. A perspective analysis and comparison are made to identify the salient aspects of each model structure. Model configuration with best characteristics is then identified based upon model quality parameters such as residual analysis, final prediction error, and fit percentages. Extensive validation to evaluate the performance of the developed model is then performed utilizing the flight dynamics data collected. Results indicate the model’s viability as the model can accurately predict the system performance at a wide range of operating conditions. Through this, to the best of our knowledge, we present for the first time a model prediction analysis, which utilizes comprehensive flight dynamics data instead of simulation work.
Keywords: Unmanned Speed Aerial Vehicle; system identification ARX; ARMAX; Box Jenkin’s; Output Error; non-linear ARX Unmanned Speed Aerial Vehicle; system identification ARX; ARMAX; Box Jenkin’s; Output Error; non-linear ARX

Share and Cite

MDPI and ACS Style

Fatima, S.K.; Abbas, M.; Mir, I.; Gul, F.; Mir, S.; Saeed, N.; Alotaibi, A.A.; Althobaiti, T.; Abualigah, L. Data Driven Model Estimation for Aerial Vehicles: A Perspective Analysis. Processes 2022, 10, 1236. https://doi.org/10.3390/pr10071236

AMA Style

Fatima SK, Abbas M, Mir I, Gul F, Mir S, Saeed N, Alotaibi AA, Althobaiti T, Abualigah L. Data Driven Model Estimation for Aerial Vehicles: A Perspective Analysis. Processes. 2022; 10(7):1236. https://doi.org/10.3390/pr10071236

Chicago/Turabian Style

Fatima, Syeda Kounpal, Manzar Abbas, Imran Mir, Faiza Gul, Suleman Mir, Nasir Saeed, Abdullah Alhumaidi Alotaibi, Turke Althobaiti, and Laith Abualigah. 2022. "Data Driven Model Estimation for Aerial Vehicles: A Perspective Analysis" Processes 10, no. 7: 1236. https://doi.org/10.3390/pr10071236

APA Style

Fatima, S. K., Abbas, M., Mir, I., Gul, F., Mir, S., Saeed, N., Alotaibi, A. A., Althobaiti, T., & Abualigah, L. (2022). Data Driven Model Estimation for Aerial Vehicles: A Perspective Analysis. Processes, 10(7), 1236. https://doi.org/10.3390/pr10071236

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