The Experimental Study of Attitude Stabilization Control for Programmable Nano Quadcopter

Year 2022, , 1 - 11, 23.03.2022

Burak Tanyeri , Zehra Ural Bayrak , Ukbe Usame Uçar

https://doi.org/10.30518/jav.1007737

Abstract

Rotary-wing nano-quadcopters are unmanned technologies used for reconnaissance and surveillance operations in many areas, especially strategic missions such as security and military operations. The main problem for these devices, which reached a wide audience with the widespread use of civilian production, is stabilization. The most important parameter affecting the stable, effective and reliable flight of these UAVs in the air is PID elements. In this study, experimental studies are carried out in [x, y, z] coordinates using a programmable Nano-quadcopter Crazyflie 2.0 drone. In order to determine the relationship between stabilization and PID control parameters of these systems, each coordinate axis is analyzed statistically. As far as is known, there is no study in the literature regarding the performance of the PID parameters of the Crazyflie 2.0 drone. At the end of the analysis study with the SPSS program, it is determined that the related drone moves with a very high level of efficiency in the "z" axis and performs the task related to the high level of efficiency on the y-axis. It is also confirmed that the drone performs poorly in the stabilization movement on the "x" axis and as a result of the analysis study, the system becomes more stable by making the necessary adjustments in the "yaw_p" parameter. Thanks to the study, it is aimed to create a decision support system for the optimization of the PID control parameters of UAVs, which are used extensively in every sector. 

Keywords

Quadcopter, Stabilization, PID Control, Statistical Analysis, Experimental Study

References

• Budaciu, C., Botezatu, N., Kloetzer, M. and Burlacu, A. (2019). On the evaluation of the Crazyflie modular quadcopter system. 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Zaragoza, Spain, 10-13 Sept.
• Candan, F., Beke, A. and Kumbasar, T. (2018). Design and deployment of fuzzy PID controllers to the nano quadcopter Crazyflie 2.0. Innovations in Intelligent systems and Applications (INISTA), Thessaloniki, Greece, 3-5 July.
• Garcia, G.A., Kim, A.R., Jackson, E., Keshmiri, S.S. and Shukla, D. (2017). Modeling and flight control of a commercial nano quadrotor. International Conference on Unmanned Aircraft Systems (ICUAS), Miami, FL, USA, 13-16 June.
• Giernacki, W., Skwierczyński, M., Witwicki, W., Wroński, P. and Kozierski, P. (2017) Crazyflie 2.0 Quadrotor as a Platform for Research and Education in Robotics and Control Engineering. 22nd International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, Poland, 28-31 Aug.
• Gong, X., Liu, J.J.R., Wang, Y. and Cui, Y. (2020). Distributed finite-time bipartite consensus of multi-agent systems on directed graphs: Theory and experiment in nano-quadcopters formation. Journal of the Franklin Institute, 357, 11953–11973.
• Greiff, M. (2017). Modelling and control of the Crazyflie quadrotor for aggressive and autonomous flight by optical flow driven state estimation. MSc Thesis, Department of Automatic Control Lund University, Sweden.
• Kaya, U., Bayrak, Z. U. and Oksuztepe, E. (2017). Fuel cell/battery hybrid powered unmanned aerial vehicle with permanent magnet synchronous motor. International Journal of Sustainable Aviation, 3 (2), 130-150.
• Kayaalp, G. T., Güney, M. Ç. and Cebeci, Z. (2015). Çoklu doğrusal regresyon modelinde değişken seçiminin zootekniye uygulanışı. Çukurova Üniversitesi, Ziraat Fakültesi Dergisi, 30 (1), 1-8.
• Kose, O. and Oktay, T. (2019). Non Simultaneous Morphing System Design for Quadrotors. European Journal of Science and Technology, 16, 577–588.
• Kose, O. and Oktay, T. (2020). Investigation of the Effect of Differential Morphing on Lateral Flight by Using PID Algorithm in Quadrotors. European Journal of Science and Technology, 18, 636–644.
• Lambert, N.O., Drew, D.S., Yaconelli, J., Levine, S., Calandra, R. and Pister, K.S.J. (2019). Low-level control of a quadrotor with deep model-based reinforcement learning. IEEE Robotics and Automation Letters, 4 (4).
• Luis, C. (2016). Design of a trajectory tracking controller for a nanoquadcopter. Technical report, Mobile Robotics and Autonomous Systems Laboratory, Polytechnique Montreal.
• Madhusudhan, M.G. (2016). Control of Crazyflie nano quadcopter using Simulink. Department of Electrical Engineering, California State University, Long Beach.
• Murmu, N. and Sharma, K.D. (2020). Trajectory tracking control for a nano quadcopter employing stochastically optimal PID control. Michael Faraday IET International Summit: MFIIS-2020, Kolkata, India, Paper ID: 75, October 03-04.
• Neumann, P.P., Hüllmann, D. and Bartholmai, M. (2019). Concept of a gas-sensitive nano aerial robot swarm for indoor air quality monitoring. Materials Today: Proceedings, 12, 470–473.
• Nguyen, H.T., Nguyen, N.T., Prodan, I. and Pereira F.L. (2020). Trajectory tracking for a multicopter under a quaternion representation. IFAC PapersOnline, 53(2), 5731-5736.
• Nithya, M. and Rashmi, M.R. (2019). Gazebo-ROS-Simulink framework for hover control and trajectory tracking of Crazyflie 2.0. IEEE Region 10 Conference (TENCON), Kochi, India, 17-20 Oct.
• Oktay, T. and Kose, O. (2019). Dynamic Modeling and Simulation of Quadrotor for Different Flight Conditions. European Journal of Science and Technology, 15, 132–142.
• Silano, G., Aucone, E. and Iannelli, L. (2018). Crazy-S: a software-in-the-loop platform for the Crazyflie 2.0 nano-quadcopter. 26th Mediterranean Conference on Control and Automation, Zadar, Croatia, June 19-22.
• Statistics II lecture notes, (Accessed: 09.12.2021) Multiple Linear Regression Analysis, https://webcache.googleusercontent.com/searchq=cache:4fWyv9CAKHMJ:https://avys.omu.edu.tr/storage/app/public/burcinseyda.corba/122288/12.HAFTA.pdf+&cd=15&hl=tr&ct=clnk&gl=tr.
• Ucar, U.Ü. and Isleyen, S.K. (2019). A new solution approach for UAV routing problem with moving target-heterogeneous fleet. Journal of Polytechnic-Politeknik Dergisi, 22 (4), 999-1016.
• Ucar, U.Ü. and Isleyen, S.K. (2017). A solution approach based on simulated annealing for the destruction of moving targets in time window by air operations. 8th International Advanced Technologies Symposium (IATS), 19-22 October, Elazig, Turkey.
• Ucar, U.Ü. and Isleyen, S.K. (2019). A meta-heuristic solution approach for the destruction of moving targets through air operations. International Journal of Industrial Engineering, 26 (6).
• Ucar, U.Ü. and Isleyen, S.K. (2020). A survey of moving target traveling salesman problem’, Human-Computer Interaction, Chapter 5, Nova Science Publishers, 107-156.
• Ucar, U.Ü., Isleyen, S.K. and Gokcen, H. (2021). Experimental analysis of Meta-Heuristic algorithms for moving customer vehicle routing problem. Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (1), 459-475.
• Wang, G., Yang, W., Zhao, N., Shen, Y. and Wang, C. (2020). An approximation-free simple controller for uncertain quadrotor systems in the presence of thrust saturation. Mechatronics, 72, 102450.
• Zhou, P. and Chen, B.M. (2022). Semi-global leader-following consensus-based formation flight of unmanned aerial vehicles. Chinese Journal of Aeronautics, 35 (1), 31-43.