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Tytuł artykułu

An adaptive pid control system for the attitude and altitude control of a quadcopter

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In adaptive model-based control systems, determining the appropriate controller gain is a complex and time-consuming task due to noise and external disturbances. Changes in the controller parameters were assumed to be dependent on the quadcopter mass, which was the process variable. A nonlinear model of the plant was used to identify the mass, employing the weighted recursive least squares (WRLS) method for online identification. The identification and control processes involved filtration using differential filters, which provided appropriate derivatives of signals. Proportional integral derivative (PID) controller tuning was performed using the Gauss–Newton optimisa-tion procedure on the plant. Differential filters played a crucial role in all the developed control systems by significantly reducing measure-ment noise. The results showed that the performance of classical PID controllers can be improved by using differential filters and gain scheduling. The control and identification algorithms were implemented in an National Instruments (NI) myRIO-1900 controller. The nonlinear model of the plant was built based on Newton’s equations.
Słowa kluczowe
Rocznik
Strony
29--39
Opis fizyczny
Bibliogr. 56 poz., rys., tab., wykr.
Twórcy
autor
  • Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Aleja Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland
  • Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Aleja Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland
  • Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Aleja Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland
Bibliografia
  • 1. Hasseni SEI, Abdou L, Glida HE. Parameters tuning of a quadrotor PID controllers by using nature-inspired algorithms. Evol Intel. 2021 Mar 1;14(1):61–73.
  • 2. Khatoon S, Nasiruddin I, Shahid M. Design and Simulation of a Hybrid PD-ANFIS Controller for Attitude Tracking Control of a Quad-rotor UAV. Arab J Sci Eng. 2017 Dec 1;42(12):5211–29.
  • 3. Kuantama E, Vesselenyi T, Dzitac S, Tarca R. PID and Fuzzy-PID Control Model for Quadcopter Attitude with Disturbance Parameter. International Journal of Computers Communications & Control. 2017 Jun 29;12(4):519–32.
  • 4. Rinaldi M, Primatesta S, Guglieri G. A Comparative Study for Control of Quadrotor UAVs. Applied Sciences. 2023 Jan;13(6):3464.
  • 5. Burggräf P, Pérez Martínez AR, Roth H, Wagner J. Quadrotors in factory applications: design and implementation of the quadrotor’s P-PID cascade control system. SN Appl Sci. 2019 Jun 14;1(7):722.
  • 6. Abdelhay S, Zakriti A. Modeling of a Quadcopter Trajectory Tracking System Using PID Controller. Procedia Manufacturing. 2019 Jan 1;32:564–71.
  • 7. Miranda-Colorado R, Aguilar LT. Robust PID control of quadrotors with power reduction analysis. ISA Transactions. 2020 Mar 1;98: 47–62.
  • 8. Okyere E, Bousbaine A, Poyi GT, Joseph AK, Andrade JM. LQR controller design for quad-rotor helicopters. The Journal of Engineer-ing. 2019;2019(17):4003–7.
  • 9. Martins L, Cardeira C, Oliveira P. Linear Quadratic Regulator for Trajectory Tracking of a Quadrotor. IFAC-PapersOnLine. 2019 Jan 1;52(12):176–81.
  • 10. Jia Z, Yu J, Mei Y, Chen Y, Shen Y, Ai X. Integral backstepping sliding mode control for quadrotor helicopter under external uncertain disturbances. Aerospace Science and Technology. 2017 Sep 1;68:299–307.
  • 11. Xiu C, Liu F, Xu G. General model and improved global sliding mode control of the four-rotor aircraft. Proceedings of the Institution of Me-chanical Engineers, Part I: Journal of Systems and Control Engineer-ing. 2018 Apr 1;232(4):383–9.
  • 12. Mofid O, Mobayen S. Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties. ISA Transactions. 2018 Jan 1;72:1–14.
  • 13. Castillo-Zamora JJ, Camarillo-GóMez KA, PéRez-Soto GI, RodríGuez-ReséNdiz J. Comparison of PD, PID and Sliding-Mode Position Controllers for V–Tail Quadcopter Stability. IEEE Access. 2018;6:38086–96.
  • 14. Liu H, Tu H, Huang S, Zheng X. Adaptive Predefined-Time Sliding Mode Control for QUADROTOR Formation with Obstacle and Inter-Quadrotor Avoidance. Sensors. 2023 Jan;23(5):2392.
  • 15. Jiang F, Pourpanah F, Hao Q. Design, Implementation, and Evalua-tion of a Neural-Network-Based Quadcopter UAV System. IEEE Transactions on Industrial Electronics. 2020 Mar;67(3):2076–85.
  • 16. El Gmili N, Mjahed M, El Kari A, Ayad H. Particle Swarm Optimiza-tion and Cuckoo Search-Based Approaches for Quadrotor Control and Trajectory Tracking. Applied Sciences. 2019 Jan;9(8):1719.
  • 17. Tanveer MH, Ahmed SF, Hazry D, Warsi FA, Joyo MK. Stabilized Controller Design for Attitude and Altitude Controlling of Quad-Rotor Under Disturbance and Noisy Conditions. AJAS. 2013 Jul 24;10(8):819–31.
  • 18. Moreno-Valenzuela J, Pérez-Alcocer R, Guerrero-Medina M, Dzul A. Nonlinear PID-Type Controller for Quadrotor Trajectory Tracking. IEEE/ASME Transactions on Mechatronics. 2018 Oct;23(5):2436–47.
  • 19. Wu Y, Hu K, Sun XM. Modeling and Control Design for Quadrotors: A Controlled Hamiltonian Systems Approach. IEEE Transactions on Vehicular Technology. 2018 Dec;67(12):11365–76.
  • 20. Kidambi KB, Tiwari M, Ijoga EO, MacKunis W. Adaptive Modified RISE-based Quadrotor Trajectory Tracking with Actuator Uncertainty Compensation [Internet]. arXiv; 2023 [cited 2023 Dec 8]. Available from: http://arxiv.org/abs/2303.10270
  • 21. Dong T, Zhang Y, Liu Y, Chen C. Quantitative Study of Load Stability of Quadrotor Based on Lyapunov Exponents. International Journal of Antennas and Propagation. 2023 Apr 19;2023:e9918890.
  • 22. Tal E, Karaman S. Accurate Tracking of Aggressive Quadrotor Trajectories Using Incremental Nonlinear Dynamic Inversion and Dif-ferential Flatness. IEEE Transactions on Control Systems Technolo-gy. 2021 May;29(3):1203–18.
  • 23. Hong JY, Chiu PJ, Pong CD, Lan CY. Attitude and Altitude Control Design and Implementation of Quadrotor Using NI myRIO. Electron-ics. 2023 Jan;12(7):1526.
  • 24. Niederliński A, Mościński J, Ogonowski Z. AdaptiveControl. PWN. Warsaw. 1995.
  • 25. Audronis T. Building Multicopter Video Drones. Packt Publishing; 2014.
  • 26. Bouabdallah S, Noth A, Siegwart R. PID vs LQ control techniques applied to an indoor micro quadrotor. In: 2004 IEEE/RSJ Internation-al Conference on Intelligent Robots and Systems (IROS) (IEEE Cat No04CH37566) [Internet]. 2004 [cited 2023 Dec 8]. p. 2451–6 vol.3.
  • 27. Janecki D. Globally stable and exponentially convergent adaptive control. International Journal of Control. 1986 Feb 1;43(2):601–13.
  • 28. Ammar NB, Gue SB, Ge JH. Modeling and Sliding Mode Control of a Quadrotor Unmanned Aerial Vehicle. 3rd International Conference on Automation, Control, Engineering and Computer Science. 2016: 834-840.
  • 29. Herrera M, Chamorro W, Gómez AP, Camacho O. Sliding Mode Control: An Approach to Control a Quadrotor. In: 2015 Asia-Pacific Conference on Computer Aided System Engineering [Internet]. 2015 [cited 2023 Dec 8]. p. 314–9.
  • 30. Rabhi A, Chadli M, Pegard C. Robust fuzzy control for stabilization of a quadrotor. 15th International Conference on Advanced Robotics (ICAR). 2011 Jun 1: 471-475.
  • 31. Szcześniak A, Szcześniak Z. Algorithmic Method for the Design of Sequential Circuits with the Use of Logic Elements. Applied Scienc-es. 2021 Jan;11(23):11100.
  • 32. Jacobsen RH, Matlekovic L, Shi L, Malle N, Ayoub N, Hageman K, et al. Design of an Autonomous Cooperative Drone Swarm for Inspec-tions of Safety Critical Infrastructure. Applied Sciences. 2023 Jan;13(3):1256.
  • 33. Cheng LL, Liu HB. Examples of quadrocopter control on ROS. In: 2015 IEEE 9th International Conference on Anti-counterfeiting, Secu-rity, and Identification (ASID) [Internet]. 2015 [cited 2023 Dec 8]. p. 92–6.
  • 34. Florek M, Huba M, Duchoň F, Šovčík J, Kajan M. Comparing ap-proaches to quadrocopter control. In: 2014 23rd International Con-ference on Robotics in Alpe-Adria-Danube Region (RAAD) [Internet]. 2014 [cited 2023 Dec 8]. 1–6.
  • 35. Holonec R, Copindean R, Dragan F, Rápolti L. Self-guided AR Drone using LabVIEW. 2016;57(5).
  • 36. Gardecki S, Giernacki W, Goslinski J, Kasinski A. An adequate mathematical model of four-rotor flying robot in the context of control simulations. Journal of Automation Mobile Robotics and Intelligent Systems [Internet]. 2014 [cited 2023 Dec 8];Vol. 8, No. 2.
  • 37. Koruba Z, Control and correction of a gyroscopic platform mounted in a flying object. Journal of Theoretical and Applied Mechanics. 2007. vol. 45, no. 1, p.41–51
  • 38. Koruba Z, Dziopa Z, Krzysztofik I. Dynamics and control of a gyro-scope-stabilized platform in a self-propelled anti-aircraft system. Journal of Theoretical and Applied Mechanics. 2010;48(1):5–26.
  • 39. Astrom K, Wittenmark B, Adaptive control, Addison-Wesley Publish-ing Company, 1989.
  • 40. Formánek I, Farana R. Experimental identification of mechanical properties of variable speed drives. In: 2017 18th International Car-pathian Control Conference (ICCC) [Internet]. 2017 [cited 2023 Dec 8]. 117–22.
  • 41. Formánek I, Farana R. Design and synthesis of control systems of material flow in industrial companies. In: 2017 18th International Car-pathian Control Conference (ICCC) [Internet]. 2017 [cited 2023 Dec 8]. 112–6.
  • 42. Viteckova M, Vitecek A, Janacova D. Robust stability and desired model method. In: 2018 Cybernetics & Informatics (K&I) [Internet]. 2018 [cited 2023 Dec 8]. 1–5.
  • 43. Viteckova M, Vitecek A, Sladka K. Controller tuning by desired model method. In: 2017 18th International Carpathian Control Conference (ICCC) [Internet]. 2017 [cited 2023 Dec 8]. 171–6.
  • 44. Viteckova M, Vitecek A. 2DOF PID controller tuning for integrating plants. In: 2016 17th International Carpathian Control Conference (ICCC) [Internet]. 2016 [cited 2023 Dec 8]. 793–7.
  • 45. Janecki D. New recursive parameter estimation algorithms with varying but bounded gain matrix. International Journal of Control. 1988 Jan 1;47(1):75–84.
  • 46. Basri A, Husain A, A. Danapalasingam K. Nonlinear Control of an Autonomous Quadrotor Unmanned Aerial Vehicle using Backstep-ping Controller Optimized by Particle Swarm Optimization. Journal of Engineering Science and Technology Review. 2015 Sep 1;8:39–45.
  • 47. Erkol HO. Attitude controller optimization of four-rotor unmanned air vehicle. International Journal of Micro Air Vehicles. 2018 Mar 1;10(1):42–9.
  • 48. Goldberg DE, Holland JH. Genetic Algorithms and Machine Learning. Machine Learning. 1988 Oct 1;3(2):95–9.
  • 49. Chandra Mohan B, Baskaran R. A survey: Ant Colony Optimization based recent research and implementation on several engineering domain. Expert Systems with Applications. 2012 Mar 1;39(4): 4618–27.
  • 50. Karaboga D, Gorkemli B, Ozturk C, Karaboga N. A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif In-tell Rev. 2014 Jun 1;42(1):21–57.
  • 51. El Gmili N, Mjahed M, El Kari A, Ayad H. Particle Swarm Optimiza-tion and Cuckoo Search-Based Approaches for Quadrotor Control and Trajectory Tracking. Applied Sciences. 2019 Jan; 9(8):1719.
  • 52. Joshi AS, Kulkarni O, Kakandikar GM, Nandedkar VM. Cuckoo Search Optimization- A Review. Materials Today: Proceedings. 2017 Jan 1;4(8):7262–9.
  • 53. Imane S, Mostafa M, Hassan A, Abdeljalil EK. Control of a quadcop-ter using reference model and genetic algorithm methods. In: 2015 Third World Conference on Complex Systems (WCCS) [Internet]. 2015 [cited 2023 Dec 8]. p. 1–6.
  • 54. LabVIEW™ . System Identification Toolkit Algorithm References. ni.com. June 2008.
  • 55. Cedro L, Janecki D., Determining of Signal Derivatives in Identifica-tion Problems -FIR Differential Filters, Acta Montanistica Slovaca, R 16, ISSN 1335-1788, 47-54, 2011.
  • 56. Cedro L, Filtry różniczkujące w układach czasu rzeczywistego, Przegląd Elektrotechniczny, ISSN 0033-2097, R. 89 NR 7/2013. 137-141.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d1ead49b-7579-4f2a-872f-e4338e92439c
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