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Identification of a quadcopter autopilot system via Box–Jenkins structure

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)

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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.

Item Type: Article (Journal)
Additional Information: 7661/77890
Uncontrolled Keywords: Prediction error method (PEM), Auto-regressive (AR) system, Box–Jenkins (BJ) model, Quadcopter Autopilot system
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Kulliyyah of Engineering
Depositing User: DR Noor Hazrin Hany Mohamad Hanif
Date Deposited: 28 Jan 2020 16:31
Last Modified: 28 Jan 2020 16:31
URI: http://irep.iium.edu.my/id/eprint/77890

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