Pengendalian Kestabilan Ketinggian pada Penerbangan Quadrotor dengan Metode PID Fuzzy

https://doi.org/10.22146/ijeis.15456

Panca Agung Kusuma(1*), Andi Dharmawan(2),

(1) 
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author

Abstract


 Quadrotor is a kind of unmanned aerial vehicle that have the ability to take of vertically and maintaining its position while flying mid-air. Flying a quadrotor sometimes needs a stable altitude to perform a specific mission. A stable altitude will make easier for pilot to control the movement of the quadrotor to certain direction.

This study designed and implemented a system that can stabilises the altitude of a quadrotor by using Fuzzy-PID method. Altitude control system needed to help pilot controls the altitude stability without adjusting the throttle. Control with PID method is a common control system to be implemented on a quadrotor. This control system has a constant that can be tuned with fuzzy logic with linguistic approach to improve the response time when compensating an error.

 The result of this study shows that Fuzzy PID control method generate a better response time compared with the PID-only method. The implementation of PID control generate an altitude stabilisation with a mean value steady state error of ±1,86 cm, whereas the PID Fuzzy generate a mean value of steady state error of ±1,22 cm.


Keywords


UAV, quadrotor, PID, fuzzy, altitude

Full Text:

PDF


References

[1] Bouabdallah, S., Noth, A. & Siegwan, R., 2004. PID vs LQ Control Techniques Applied to an Indoor Micro Quadrotor.

[2]      Fatan, M., Sefidgari, B. L., & Barenji, A. V. (2013). An Adaptive Neuro PID for Controlling the Altitude of Quadcopter Robot Output of Plant, 662–665. http://doi.org/10.13140/RG.2.1.2896.0804

[3]      Mehranpour, M.R., 2013. A New Fuzzy Adaptive Control for a Quadrotor Flying Robot.

[4]Raza, S.A. & Gueaieb, W., 2010. Intelligent Flight Control of an Autonomous Quadrotor.

[5]Ogata, K., 2010, Modern Control Engineering Fifth Edition, Fifth, Prentice Hall, New Jersey.

[6] Naba, A., 2009. Belajar Cepat Fuzzy Logic Menggunakan Matlab, ANDI OFFSET, Yogyakarta.

 

[7] Zadeh, L.A., 2004. Fuzzy Logic Systems: Origin, Concepts, and Trends.University of Carolina, Berkeley.

 

[8] Santos, M., Lopez, V., Morata, F., 2010, Intelegent Fuzzy Controller of Quadrotor, Universidad Complutense, Spain.

 

[9] Leong, B.T.M., Low, S.M. dan Ooi, M.P.-L., 2012, Low-Cost Microcontroller-based Hover Control Design of a Quadcopter, Procedia Engineering, [Online] 41 (Iris), 458–464, tersedia di DOI:10.1016/j.proeng.2012.07.198.

 

[10] Pogram, D.F., 2014, Implementasi Metode Penala Konstanta PID Berdasarkan Logika Fuzzy pada Quadrotor, Skripsi, FMIPA Universitas Gadjah Mada, Yogyakarta.



DOI: https://doi.org/10.22146/ijeis.15456

Article Metrics

Abstract views : 213 | views : 76

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 IJEIS - Indonesian Journal of Electronics and Instrumentation Systems

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Indonesian Journal of Electronics and Instrumentations Systems
(IJEIS) ISSN 2088-3714 (print); ISSN 2460-7681 (online)
is a scientific journal the results of Electronics
and Instrumentations Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijeis.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijeis


Creative Commons License
IJEIS by http://jurnal.ugm.ac.id/ijeis is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1
View My Stats2