Optimization of Quadrotor’s Thrust and Torque Coefficients and Simulation with Matlab/Simulink

Öz

In this study, the thrust forces and torque values were experimentally measured which determine the quadrotor dynamics majorly and and optimization was performed on the the quadrotor simulation model. The electronic speed controller, which regulates the speed of the rotors, is controlled in the frequencies range from 1100 to 2000 by pulse width modulation (PWM) method. Thrust force, torque value and rotor speed measurements were experimentally performed on motor and propeller pair. The regression analyzes of these parameters were performed according to the rotor speed. Regression analyzes were performed with linear, quadratic, cubic and constant coefficient methods. The obtained regression equations were applied to Matlab/Simulink quadrotor model and the errors in the quadrotor trajectory tracking were compared. It has been observed that the thrust and torque values obtained from momentum theorem have high deviation in 2-meter trajectory tracking. It has been observed that using the quadratic regression method to determine thrust force and using the cubic regression method to determine torque value minimize the amount of error in trajectory tracking.

Anahtar Kelimeler

• UAV,quadrotor,PID control,flight dynamics

Quadrotor İtme ve Tork Katsayılarının Optimizasyonu ve Matlab/Simulink ile Simülasyonu

Öz

Bu çalışmada,  quadrotorların dinamiğini büyük ölçüde belirleyen itme ve tork kuvvetleri deneysel olarak ölçülmüş ve quadrotorun simülasyon modeli üzerinden optimizasyonu gerçekleştirilmiştir. Motor devrinin kontrolünde elektronik hız kontrol kartı kullanılmış ve darbe genişlik modülasyon (DGM) metodu ile 1100-2000 frekans aralığında kontrol edilmiştir. Motor ve pervane çiftinin itme kuvveti, tork değeri ve devir sayısı ölçümleri deneysel olarak gerçekleştirilmiştir. Bu deneysel verilerin regresyon analizleri motor devrine bağlı olarak gerçekleştirilmiştir. Regresyon analizleri doğrusal, karesel, kübik ve sabit katsayılı metodlar ile gerçekleştirilmiştir. Regresyon ile elde edilen denklemler Matlab/Simulink’te oluşturulan quadrotor modeline uygulanmış ve quadrotorun dairesel yörünge takibindeki hatalar kıyaslanmıştır. Momentum teoreminden elde edilen itme kuvveti ve tork değerlerinin 2 metrelik yörünge takibinde yüksek hata miktarına sahip olduğu gözlenmiştir. İtme kuvvetinin belirlenmesinde karesel regresyon yönteminin kullanılması ve tork değerinin belirlenmesinde kübik regresyon yönteminin kullanılması, yörünge takibindeki hata miktarını en aza indirdiği gözlenmiştir.  

Anahtar Kelimeler

• İHA,Quadrotor,PID Kontrol,Uçuş Dinamiği

Kaynakça

1. Referans1 Chen X., Zhang. M., and Yang Y.-D., “Study of an Intelligent PID Attitude Controller for UAV”, Journal of Nanjing University of Aeronautics & Astronautics, 6, 76-83, 2003.
2. Referans2 Lee D., Kim H. J., and Sastry S., “Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter”, International Journal of Control Automation and Systems, 7(3), 419-428, 2009.
3. Referans3 Nicol C., Macnab C. J. B., and Ramirez-Serrano A., “Robust neural network control of a quadrotor helicopter”, Canadian Conference on Electrical and Computer Engineering, 1, 1233-1237, 2008.
4. Referans4 Santos M., López V., and Morata F., “Intelligent fuzzy controller of a quadrotor”, IEEE International Conference on Intelligent Systems and Knowledge Engineering 141-146, 2010.
5. Referans5 Madani T. and Benallegue A., “Adaptive control via backstepping technique and neural networks of a quadrotor helicopter”, IFAC Proceedings Volumes, 41(1), 6513-6518, 2008.
6. Referans6 Bouabdallah S. “Design and control of quadrotors with application to autonomous flying”, Ph.D Thesis, École. Polytechnique and Federale De Lausanne, Siegwart, Roland, 2007.
7. Referans7 Tomashevich S. and Belyavskyi A., “Passification Based Simple Adaptive Control Of Quadrotor”, IFAC-PapersOnLine, 49(13), 281-286, 2016.
8. Referans8 Shao X., Liu J., and Wang H., “Robust back-stepping output feedback trajectory tracking for quadrotors via extended state observer and sigmoid tracking differentiator”, Mechanical Systems and Signal Processing, 104, 631-647, 2018.

9. Referans9 Cabecinhas D, Cunha R., and Silvestre C. “A trajectory tracking control law for a quadrotor with slung load”, Automatica, 106, 384-389, 2019.
10. Referans10 Ryll M., Bulthoff H. H., and Giordano P. R., “A Novel Overactuated Quadrotor UAV: Modeling, Control and Experimental Validation”, IEEE Transactions on Control Systems Technology, 23(2), 540-556, 2015.
11. Referans11 T. P. Shenoy, K. Praveen Shenoy, L. Khan, S. Aziz, S. Afran, and K. Kumar, “Design and development of a novel triphibian quadcopter,” International Journal of Engineering & Technology, 7(2.21), 1-4, 2018.
12. Referans12 Oosedo A., Konno A., Matsumoto T., Go K., Masuko K., and Uchiyama M., “Design and attitude control of a quad-rotor tail-sitter vertical takeoff and unmanned aerial vehicle”, Advanced Robotics, 26(3-4), 307-326, 2012.
13. Referans13 Nandakumar G., Srinivasan A., and Thondiyath A., “Theoretical and Experimental Investigations on the Effect of Overlap and Offset on the Design of a Novel Quadrotor Configuration, VOOPS”, Journal of Intelligent & Robotic Systems, 92(3-4), 615-628, 2018.
14. Referans14 Badr S., Mehrez O., and Kabeel A. E., “A novel modification for a quadrotor design,” International Conference on Unmanned Aircraft Systems, 702–710, 2016.
15. Referans15 Leishman, J. G., “Principles of helicopter aerodynamics”, Cambridge Aerospace Series, Cambridge University Press, 2016.
16. Referans16 Ercan Y., “İleri dinamik”, ISBN: 978-605-030-981-2, 2014.