Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle

Improving quadcopter control systems poses significant challenges in unmanned flight technology development. Key issues include the intricate nature of PID and Kalman filter parameter settings, necessitating profound knowledge of system dynamics and sensor properties. Furthermore, successfully integ...

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Main Authors: Ernando Rizki Dalimunthe, Novan Dwiki Ananda, Jaka Persada Sembiring, Muhammad Anwar Sadat Faidar, Elka Pranita, Akhmad Jayadi, Novia Utami Putri
Format: Article
Language:English
Published: Institut Teknologi Dirgantara Adisutjipto 2025-02-01
Series:Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls
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Online Access:https://ejournals.itda.ac.id/index.php/avitec/article/view/2743
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author Ernando Rizki Dalimunthe
Novan Dwiki Ananda
Jaka Persada Sembiring
Muhammad Anwar Sadat Faidar
Elka Pranita
Akhmad Jayadi
Novia Utami Putri
author_facet Ernando Rizki Dalimunthe
Novan Dwiki Ananda
Jaka Persada Sembiring
Muhammad Anwar Sadat Faidar
Elka Pranita
Akhmad Jayadi
Novia Utami Putri
author_sort Ernando Rizki Dalimunthe
collection DOAJ
description Improving quadcopter control systems poses significant challenges in unmanned flight technology development. Key issues include the intricate nature of PID and Kalman filter parameter settings, necessitating profound knowledge of system dynamics and sensor properties. Furthermore, successfully integrating the Kalman Filter with PID control demands meticulous coordination to optimize state estimation precision and system responsiveness. This research emphasizes the incorporation of the Kalman filter into PID-based control for quadcopter pitch angle regulation. The Proportional-Integral-Derivative (PID) approach governs pitch angle, augmented by the Kalman Filter, to enhance estimation accuracy and mitigate sensor uncertainty. Optimal outcomes during system response testing were achieved with parameters of Kp at 2.95, Ki at 0.23, and Kd at 0.02, resulting in superior oscillatory response, including a 9-degree overshoot, a 5-second rise time, a 15-second settling time, and a 0.15-degree steady-state error, showcasing effective regulation of the quadcopter pitch angle. A concurrent observation during testing indicated that including the Kalman filter led to a significantly reduced overshoot compared to tests without it; conversely, the settling time experienced considerable acceleration, while measurement accuracy in the steady-state condition improved by 50%.
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2715-2626
language English
publishDate 2025-02-01
publisher Institut Teknologi Dirgantara Adisutjipto
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series Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls
spelling doaj-art-d9eeb44cdcc9431f9dc58fbb116752422025-08-20T02:21:13ZengInstitut Teknologi Dirgantara AdisutjiptoAviation Electronics, Information Technology, Telecommunications, Electricals, Controls2685-23812715-26262025-02-0171415110.28989/avitec.v7i1.27431014Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch AngleErnando Rizki Dalimunthe0Novan Dwiki Ananda1Jaka Persada Sembiring2Muhammad Anwar Sadat Faidar3Elka Pranita4Akhmad Jayadi5Novia Utami Putri6Universitas Teknokrat IndonesiaUniversitas Teknokrat IndonesiaUniversitas Teknokrat IndonesiaUniversitas Teknokrat IndonesiaUniversitas Teknokrat IndonesiaPoliteknik Negeri LampungPoliteknik Negeri LampungImproving quadcopter control systems poses significant challenges in unmanned flight technology development. Key issues include the intricate nature of PID and Kalman filter parameter settings, necessitating profound knowledge of system dynamics and sensor properties. Furthermore, successfully integrating the Kalman Filter with PID control demands meticulous coordination to optimize state estimation precision and system responsiveness. This research emphasizes the incorporation of the Kalman filter into PID-based control for quadcopter pitch angle regulation. The Proportional-Integral-Derivative (PID) approach governs pitch angle, augmented by the Kalman Filter, to enhance estimation accuracy and mitigate sensor uncertainty. Optimal outcomes during system response testing were achieved with parameters of Kp at 2.95, Ki at 0.23, and Kd at 0.02, resulting in superior oscillatory response, including a 9-degree overshoot, a 5-second rise time, a 15-second settling time, and a 0.15-degree steady-state error, showcasing effective regulation of the quadcopter pitch angle. A concurrent observation during testing indicated that including the Kalman filter led to a significantly reduced overshoot compared to tests without it; conversely, the settling time experienced considerable acceleration, while measurement accuracy in the steady-state condition improved by 50%.https://ejournals.itda.ac.id/index.php/avitec/article/view/2743quadcopterpidkalman filter
spellingShingle Ernando Rizki Dalimunthe
Novan Dwiki Ananda
Jaka Persada Sembiring
Muhammad Anwar Sadat Faidar
Elka Pranita
Akhmad Jayadi
Novia Utami Putri
Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls
quadcopter
pid
kalman filter
title Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle
title_full Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle
title_fullStr Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle
title_full_unstemmed Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle
title_short Implementation of Kalman Filter on PID Based Quadcopter for Controlling Pitch Angle
title_sort implementation of kalman filter on pid based quadcopter for controlling pitch angle
topic quadcopter
pid
kalman filter
url https://ejournals.itda.ac.id/index.php/avitec/article/view/2743
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