Identification of a quadcopter autopilot system via Box–Jenkins structure

This paper presents a method to precisely model a four rotor unmanned aerial vehicle, widely known as quadcopter autopilot system. Common system identification methods limit quadcopter models into first or second order systems, and do not count for noise characteristics. This leads to poor predictio...

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Main Authors:	Bnhamdoon, Omar Awadh Ahmed, Mohamad Hanif, Noor Hazrin Hany, Akmeliawati, Rini
Format:	Article
Language:	English English
Published:	Springer Nature 2020
Subjects:	TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Online Access:	http://irep.iium.edu.my/77890/ http://irep.iium.edu.my/77890/ http://irep.iium.edu.my/77890/ http://irep.iium.edu.my/77890/1/77890_Identification%20of%20a%20quadcopter%20autopilot%20-%20in%20press.pdf http://irep.iium.edu.my/77890/2/77890_Identification%20of%20a%20quadcopter%20autopilot%20-SCOPUS%20in%20press.pdf

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spelling	iium-778902020-01-28T08:31:04Z http://irep.iium.edu.my/77890/ Identification of a quadcopter autopilot system via Box–Jenkins structure Bnhamdoon, Omar Awadh Ahmed Mohamad Hanif, Noor Hazrin Hany Akmeliawati, Rini TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices This paper presents a method to precisely model a four rotor unmanned aerial vehicle, widely known as quadcopter autopilot system. Common system identification methods limit quadcopter models into first or second order systems, and do not count for noise characteristics. This leads to poor prediction accuracy of its longitudinal and lateral motion dynamics that ultimately affects the aircraft stabilization during flight and landing. To improve the quality of the estimated models, we utilized a statistically suitable discrete-time linear Box–Jenkins structure to model the plant and noise characteristics of the horizontal subsystems of a quadcopter autopilot system. The models were estimated using flight data acquired when the system were provided with pseudo-random binary sequence input. In this proposed method, by employing the prediction error method and least squares approach, the aircraft dynamics could be modeled up until the fifth order. The normalized root mean square fitness value showed that the predicted model output matches the experimental flight data by 94.72% in the one-step-ahead prediction test, and 84.52% in the infinite-step-ahead prediction test. These prediction results demonstrated an improvement of 52.8% when compared with a first and second order model structures proposed in previous works for the same quadcopter model. The output from this research works confirmed the effectiveness of the proposed method to adequately capture the autopilot dynamics and accurately predict the quadcopter outputs. These would greatly assist in designing robust flight controllers for the autopilot system. Springer Nature 2020-01-02 Article PeerReviewed application/pdf en http://irep.iium.edu.my/77890/1/77890_Identification%20of%20a%20quadcopter%20autopilot%20-%20in%20press.pdf application/pdf en http://irep.iium.edu.my/77890/2/77890_Identification%20of%20a%20quadcopter%20autopilot%20-SCOPUS%20in%20press.pdf Bnhamdoon, Omar Awadh Ahmed and Mohamad Hanif, Noor Hazrin Hany and Akmeliawati, Rini (2020) Identification of a quadcopter autopilot system via Box–Jenkins structure. International Journal of Dynamics and Control. pp. 1-16. ISSN 2195-268X E-ISSN 2195-2698 (In Press) https://link.springer.com/article/10.1007/s40435-019-00605-x 10.1007/s40435-019-00605-x
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Bnhamdoon, Omar Awadh Ahmed Mohamad Hanif, Noor Hazrin Hany Akmeliawati, Rini Identification of a quadcopter autopilot system via Box–Jenkins structure
description	This paper presents a method to precisely model a four rotor unmanned aerial vehicle, widely known as quadcopter autopilot system. Common system identification methods limit quadcopter models into first or second order systems, and do not count for noise characteristics. This leads to poor prediction accuracy of its longitudinal and lateral motion dynamics that ultimately affects the aircraft stabilization during flight and landing. To improve the quality of the estimated models, we utilized a statistically suitable discrete-time linear Box–Jenkins structure to model the plant and noise characteristics of the horizontal subsystems of a quadcopter autopilot system. The models were estimated using flight data acquired when the system were provided with pseudo-random binary sequence input. In this proposed method, by employing the prediction error method and least squares approach, the aircraft dynamics could be modeled up until the fifth order. The normalized root mean square fitness value showed that the predicted model output matches the experimental flight data by 94.72% in the one-step-ahead prediction test, and 84.52% in the infinite-step-ahead prediction test. These prediction results demonstrated an improvement of 52.8% when compared with a first and second order model structures proposed in previous works for the same quadcopter model. The output from this research works confirmed the effectiveness of the proposed method to adequately capture the autopilot dynamics and accurately predict the quadcopter outputs. These would greatly assist in designing robust flight controllers for the autopilot system.
format	Article
author	Bnhamdoon, Omar Awadh Ahmed Mohamad Hanif, Noor Hazrin Hany Akmeliawati, Rini
author_facet	Bnhamdoon, Omar Awadh Ahmed Mohamad Hanif, Noor Hazrin Hany Akmeliawati, Rini
author_sort	Bnhamdoon, Omar Awadh Ahmed
title	Identification of a quadcopter autopilot system via Box–Jenkins structure
title_short	Identification of a quadcopter autopilot system via Box–Jenkins structure
title_full	Identification of a quadcopter autopilot system via Box–Jenkins structure
title_fullStr	Identification of a quadcopter autopilot system via Box–Jenkins structure
title_full_unstemmed	Identification of a quadcopter autopilot system via Box–Jenkins structure
title_sort	identification of a quadcopter autopilot system via box–jenkins structure
publisher	Springer Nature
publishDate	2020
url	http://irep.iium.edu.my/77890/ http://irep.iium.edu.my/77890/ http://irep.iium.edu.my/77890/ http://irep.iium.edu.my/77890/1/77890_Identification%20of%20a%20quadcopter%20autopilot%20-%20in%20press.pdf http://irep.iium.edu.my/77890/2/77890_Identification%20of%20a%20quadcopter%20autopilot%20-SCOPUS%20in%20press.pdf
first_indexed	2023-09-18T21:49:49Z
last_indexed	2023-09-18T21:49:49Z
_version_	1777413694392631296

Identification of a quadcopter autopilot system via Box–Jenkins structure

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