PID Control Tuning Based on Wind Speed Sensor in Flying Robot

Fadlur Rahman T Hasan, Son Ali Akbar

Abstract


The problem that is often faced by flying robots when carrying out the Vertical Take Off Landing (VTOL) process is the lack of stability of the vehicle due to differences in wind speed at any time. This is because the PID that has been pre-tuned is the PID at a certain wind speed and it is possible that during the race the wind speed suddenly changes, causing the vehicle to be less stable in carrying out the mission. Therefore, this study proposes a PID Control Tuning Control system based on the Wind Speed Sensor. In experiments that have been carried out with anemometer readings of 1-5 m/s, the ideal tuning results are obtained with each parameter P_roll = 0.1453, I_roll = 0.0892, D_roll = 0.004, P_pitch = 0.144, I_pitch = 0.09, D_pitch = 0.004, P_yaw = 0.184, I_yaw = 0.0184, D_yaw = 0.00309. In experiments with anemometer readings of 6-10 m/s, the ideal tuning results were obtained with each parameter P_roll = 0.148, I_roll = 0.0905, D_roll = 0.004, P_pitch = 0.1444, I_pitch = 0.09, D_pitch = 0.004, P_yaw = 0.1867, I_yaw = 0.0181, D_yaw = 0.0037. In an experiment with an anemometer reading of 11-15 m/s, the ideal tuning results were obtained with each parameter P_roll = 0.1494, I_roll = 0.09, D_roll = 0.004, P_pitch = 0.1457, I_pitch = 0.0902, D_pitch = 0.004, P_yaw = 0.1894, I_yaw = 0.018, D_yaw = 0.0037. PID adjustment based on this anemometer sensor utilizes the latest real-time wind speed data to support the robot in order to overcome instability in certain wind conditions by tuning PID so that the vehicle can maintain stability when carrying out certain missions.

Keywords


KRTI; VTOL; PID; Anemometer; Tuning; Flying Robot

Full Text:

PDF

References


S. J. Haddadi, P. Zarafshan, M. Dehghani, “A coaxial quadrotor flying robot: Design, analysis and control implementation,” Aerospace Science and Technology, vol. 120, p. 107260, 2022, https://doi.org/10.1016/j.ast.2021.107260.

X. U. Wenfu, P. A. N. Erzhen, L. I. U. Juntao, L. I. Yihong, Y. U. A. N. Han, “Flight control of a large-scale flapping-wing flying robotic bird: System development and flight experiment,” Chinese Journal of Aeronautics, vol. 35, no. 2, pp. 235-249, 2022, https://doi.org/10.1016/j.cja.2021.03.009.

C. B. Jabeur, H. Seddik, “Optimized neural networks-PID controller with wind rejection strategy for a Quad-Rotor,” Journal of Robotics and Control (JRC), vol. 3, no. 1, pp. 62-72, 2022, https://doi.org/10.18196/jrc.v3i1.11660.

B. Zhang, S. Furukawa and H. Lim, "Study on Automatic PID Gain Adjustment for a Four-rotor Flying Robot using Neural Network," 2019 4th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), pp. 104-108, 2019, https://doi.org/10.1109/ACIRS.2019.8936012.

J. Michalski, M. Retinger, P. Kozierski and W. Giernacki, "Position Control of Crazyflie 2.1 Quadrotor UAV Based on Active Disturbance Rejection Control," 2023 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1106-1113, 2023, https://doi.org/10.1109/ICUAS57906.2023.10156505.

T. Susanto, M. Bayu Setiawan, A. Jayadi, F. Rossi, A. Hamdhi and J. Persada Sembiring, "Application of Unmanned Aircraft PID Control System for Roll, Pitch and Yaw Stability on Fixed Wings," 2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE), pp. 186-190, 2021, https://doi.org/10.1109/ICOMITEE53461.2021.9650314.

M. Esfandiari and M. A. Amiri Atashgah, "Reinforcement Learning Control of an Aerial Robot Based on a Tuned Proximal Policy Optimization in Takeoff and Hover Phases," 2022 10th RSI International Conference on Robotics and Mechatronics (ICRoM), pp. 165-171, 2022, https://doi.org/10.1109/ICRoM57054.2022.10025140.

V. P. Tran, F. Santoso, M. A. Garratt and I. R. Petersen, "Distributed Formation Control Using Fuzzy Self-Tuning of Strictly Negative Imaginary Consensus Controllers in Aerial Robotics," in IEEE/ASME Transactions on Mechatronics, vol. 26, no. 5, pp. 2306-2315, 2021, https://doi.org/10.1109/TMECH.2020.3036829.

M. Mazinani, P. Zarafshan, M. Dehghani, H. Etezadi, K. Vahdati and G. Chegini, "Modeling and Control of a Pollinator Flying Robot," 2021 9th RSI International Conference on Robotics and Mechatronics (ICRoM), pp. 548-553, 2021, https://doi.org/10.1109/ICRoM54204.2021.9663526.

A. S. Priambodo, F. Arifin, A. Nasuha, A. Winursito, “Face Tracking for Flying Robot Quadcopter based on Haar Cascade Classifier and PID Controller,” Journal of Physics: Conference Series, vol. 2111, no. 1, p. 012046, 2021, https://doi.org/10.1088/1742-6596/2111/1/012046.

I. Trenev, A. Tkachenko, A. Kustov, “Movement stabilization of the parrot mambo quadcopter along a given trajectory based on PID controllers,” IFAC-PapersOnLine, vol. 54, no. 13, pp. 227-232, 2021, https://doi.org/10.1016/j.ifacol.2021.10.450.

J. Mou, W. Zhang, K. Zheng, Y. Wang, C. Wu, “More detailed disturbance measurement and active disturbance rejection altitude control for a flapping wing robot under internal and external disturbances,” Journal of Bionic Engineering, vol. 19, no. 6, 1722-1735, 2022, https://doi.org/10.1007/s42235-022-00236-7.

A. Baba, B. Alothman, “A fuzzy logic-based stabilization system for a flying robot, with an embedded energy harvester and a visual decision-making system,” Robotics and Autonomous Systems, pp. 104471, 2023, https://doi.org/10.1016/j.robot.2023.104471.

M. Maier, M. Keppler, C. Ott and A. Albu-Schäffer, "Adaptive Air Density Estimation for Precise Tracking Control and Accurate External Wrench Observation for Flying Robots," IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1445-1452, 2020, https://doi.org/10.1109/LRA.2020.2967333.

M. Taherinezhad, A. Ramirez-Serrano, and A. Abedini, “Robust Trajectory-Tracking for a Bi-Copter Drone Using INDI: A Gain Tuning Multi-Objective Approach,” Robotics, vol. 11, no. 5, p. 86, 2022, http://dx.doi.org/10.3390/robotics11050086.

M. Pimentel and M. Basiri, "A Bimodal Rolling-Flying Robot for Micro Level Inspection of Flat and Inclined Surfaces," in IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 5135-5142, 2022, https://doi.org/10.1109/LRA.2022.3154027.

A. H. C. Abantas, W. A. Sabellona and C. J. O. Salaan, "Design of a Rule-Based Tuned PID Controller for Tether Management of a Suspended Tethered UAV," 2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), pp. 1-6, 2022, https://doi.org/10.1109/HNICEM57413.2022.10109555.

D. Baidya, S. Dhopte and M. Bhattacharjee, "Sensing System Assisted Novel PID Controller for Efficient Speed Control of DC Motors in Electric Vehicles," IEEE Sensors Letters, vol. 7, no. 1, pp. 1-4, 2023, https://doi.org/10.1109/LSENS.2023.3234400.

A. Khalil, M. A. Jaradat, S. Mukhopadhyay and M. F. Abdel-Hafez, "Autonomous Control of a Hybrid Rolling and Flying Caged Drone for Leak Detection in HVAC Ducts," IEEE/ASME Transactions on Mechatronics, pp. 1-13, 2023, https://doi.org/10.1109/TMECH.2023.3279870.

D. Horla, W. Giernacki, T. Báča, V. Spurny, M. Saska, “AL-TUNE: A family of methods to effectively tune UAV controllers in in-flight conditions,” Journal of Intelligent & Robotic Systems, vol. 103, no. 5, 2021, https://doi.org/10.1007/s10846-021-01441-y.




DOI: https://doi.org/10.59247/csol.v1i3.56

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Fadlur Rahman T Hasan, Son Ali Akbar

 
Control Systems and Optimization Letters
ISSN: 2985-6116
Website: https://ejournal.csol.or.id/index.php/csol
Email: alfian_maarif@ieee.org
Publisher: Peneliti Teknologi Teknik Indonesia
Address: Jl. Empu Sedah No. 12, Pringwulung, Condongcatur, Kec. Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta 55281, Indonesia