نوع مقاله : علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشکده مهندسی هوافضا، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

2 استادیار، دانشکده مهندسی هوافضا، دانشگاه خواجه نصیرالدین طوسی، تهران، ایران

چکیده

در این مقاله، استفاده از کنترل‌کننده PID جهت کنترل یک مدل از کوادروتور دارای دینامیک غیرخطی، مورد بررسی قرار می‌گیرد. در همین راستا، چهار روش متمایز جهت تنظیم پارامترهای این کنترلر مورد بررسی و مقایسه قرار می‌گیرد. این چهار تکنیک شامل تکنیک‌های برخط الگوریتم شبکه عصبی، استنتاج فازی و تکنیک‌های خارج خط الگوریتم بهینه‌سازی ژنتیک و تجمع ذرات می‌گردند. در پایان اما با توجه به نتایج حاصل از شبیه‌سازی عددی و نیز نتایج حاصل از مقایسه یک تابع هزینه پیش‌تعریف مربعی محاسبه شده در هریک از حالات استفاده از این تکنیک‌های تنظیم پارامترها در حضور یک اغتشاش نسبتاً بزرگ با دامنه و فرکانس انتخاب شده که در کل زمان شبیه‌سازی، سیستم را تحت تأثیر قرار می‌دهد، نشان داده می‌شود بطور کلی، رسته‌ی الگوریتم‌های برخط، به ویژه با وجود اغتشاش مذکور، از آن‌جا که ضرایب کنترلی سیستم حلقه-بسته را در هر گام زمانی از شبیه‌سازی عددی، به صورت لحظه‌ای بروزرسانی می‌کنند، عملکرد بهتری در کنترل دینامیک سیستم از خود نشان می‌دهد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Intelligent Tuning PID Controller, Simulation and Comparison for a Quadrotor

نویسندگان [English]

  • Mana Ghanifar 1
  • Milad Kamzan 1
  • Morteza Tayefi 2

1 PhD Student, Department of Aerospace Engineering, K. N. Toosi University of Technology, Tehran, Iran

2 Assistant Professor, Department of Aerospace Engineering, K. N. Toosi University of Technology, Tehran, Iran

چکیده [English]

n this paper, the use of PID controller to control a model of a quadrotor with nonlinear dynamics is investigated. In this regard, after presenting the designed nonlinear dynamic quadrotor model, four distinct methods for adjusting the parameters of this controller are examined and compared. These four techniques, which are classified into two categories, online and offline, include online techniques of neural network and fuzzy inference, and offline techniques of genetic and particle swarm optimization algorithms. Finally according to the results of numerical simulations and the results of comparing a predefined squared cost function calculated in each case, in the presence of a relatively large disturbance with amplitude and frequency that is selected in the whole time simulation affects the system, shown in general, the order online algorithms, especially despite the mentioned disturbance, have better performance in controlling the dynamics of the system because they update the control coefficients of the closed-loop system momentarily in each step of numerical simulation.

کلیدواژه‌ها [English]

  • PID controller
  • Quadrotor
  • Genetic algorithm
  • Fuzzy algorithm
  • Neural algorithm
[1]  S. Gupte, P. I. T. Mohandas, and J. M. Conrad, "A survey of quadrotor unmanned aerial vehicles," 2012 Proceedings of IEEE Southeastcon, pp. 1-6, 2012, https://doi.org/10.1109/SECon.2012.6196930
 [2] S. N. Ghazbi, Y. Aghli, M. Alimohammadi, and A. A. Akbari, "Quadrotors unmanned aerial vehicles: A review," International journal on smart sensing and Intelligent Systems, vol. 9, no. 1, pp. 309-333, 2016, https://doi.org/10.21307/ijssis-2017-872
 [3] M. Ghanifar, M. Kamzan, and M. Tayefi, "Coefficient Tuning of Quadrotor Feedback-linearization Controller by Different Intelligent Methods," in 20th International Conference of Iranian Aerospace, 2022.
[4] L. Li, L. Sun, and J. Jin, "Survey of advances in control algorithms of quadrotor unmanned aerial vehicle," in 2015 IEEE 16th international conference on communication technology (ICCT), 2015, pp. 107-111: IEEE, https://doi.org/10.1109/ICCT.2015.7399803
[5]  J. Kim, S. A. Gadsden, and S. A. Wilkerson, "A comprehensive survey of control strategies for autonomous quadrotors," Canadian Journal of Electrical and Computer Engineering, vol. 43, no. 1, pp. 3-16, 2019, https://doi.org/10.1109/CJECE.2019.2920938
[6]  H. Kazemi and S. Elahian, "Challenges and Opportunities of Drone Development in Iran," Journal of Technology in Aerospace Engineering, vol. 4, no. 2, pp. 64-45, 2020.
[7] N. S. Özbek, M. Önkol, and M. Ö. Efe, "Feedback control strategies for quadrotor-type aerial robots: a survey," Transactions of the Institute of Measurement and Control, vol. 38, no. 5, pp. 529-554, 2016, https://doi.org/10.1177/0142331215608427
[8] A. Zulu and S. John, "A Review of Control Algorithms for Autonomous Quadrotors," Library (Lond), pp. 547-556, 2009, https://doi.org/10.4236/ojapps.2014.414053
[9] Y. Li and S. Song, "A survey of control algorithms for quadrotor unmanned helicopter," in 2012 IEEE fifth international conference on advanced computational intelligence (ICACI), 2012, pp. 365-369: IEEE, https://doi.org/10.1109/ICACI.2012.6463187
 [10] H. Mo and G. Farid, "Nonlinear and adaptive intelligent control techniques for quadrotor uav–a survey," Asian Journal of Control, vol. 21, no. 2, pp. 989-1008, 2019, doi: 10.1002/asjc.1758.
[11] R. Fessi and S. Bouallègue, "LQG controller design for a quadrotor UAV based on particle swarm optimisation," International Journal of Automation and Control, vol. 13, no. 5, pp. 569-594, 2019.
[12] B. Whitehead and S. Bieniawski, "Model reference adaptive control of a quadrotor UAV," in AIAA Guidance, Navigation, and Control Conference, 2010, https://doi.org/10.2514/6.2010-8148
[13] G. V. Raffo, M. G. Ortega, and F. R. Rubio, "MPC with nonlinear ℋ∞ control for path tracking of a quad-rotor helicopter," IFAC Proceedings Volumes, vol. 41, no. 2, pp. 8564-8569, 2008.
[14 C. Nicol, C. Macnab, and A. Ramirez-Serrano, "Robust adaptive control of a quadrotor helicopter," Mechatronics, vol. 21, no. 6, pp. 927-938, 2011, https://doi.org/10.1016/j.mechatronics.2011.02.007
 [15] M. K. Shaik and J. F. Whidborne, "Robust sliding mode control of a quadrotor," in 2016 UKACC 11th International Conference on Control (CONTROL), 2016, pp. 1-6: IEEE.
[16] M. Santos, V. Lopez, and F. Morata, "Intelligent fuzzy controller of a quadrotor," in 2010 IEEE international conference on intelligent systems and knowledge engineering, 2010, pp. 141-146: IEEE. https://doi.org/10.1109/ISKE.2010.5680812
 
[17] M. Zareb, R. Ayad, and W. Nouibat, "Fuzzy-PID hybrid control system to navigate an autonomous mini-Quadrotor," in 3rd international conference on systems and control, 2013, pp. 906-913: IEEE, https://doi.org/10.1109/ICoSC.2013.6750965
 [18] J. Gómez-Avila, C. López-Franco, A. Y. Alanis, and N. Arana-Daniel, "Control of Quadrotor using a Neural Network based PID," in 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 2019, pp. 1-6: IEEE, https://doi.org/10.1109/LA-CCI.2018.8625222
[19] A. Alkamachi and E. Erçelebi, "Modelling and genetic algorithm based-PID control of H-shaped racing quadcopter," Arabian Journal for Science and Engineering, vol. 42, pp. 2777-2786, 2017, https://doi.org/10.1007/s13369-017-2433-2
[20] A. Noordin, M. M. Basri, Z. Mohamed, and A. Z. Abidin, "Modelling and PSO fine-tuned PID control of quadrotor UAV," Int. J. Adv. Sci. Eng. Inf. Technol, vol. 7, no. 4, pp. 1367-1373, 2017, https://doi.org/10.18517/ijaseit.7.4.3141
[21] S. Bouabdallah, "Design and control of quadrotors with application to autonomous flying," Epfl2007.