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Modeling and Simulation of Quadcopter Using Self-tuning Fuzzy-PI Controller

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Mobile Robot: Motion Control and Path Planning

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1090))

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Abstract

Helicopters, commonly known as quadrotors (UAVs), are popular unmanned aerial vehicles. Despite their small size and high stability, they are used in a variety of applications. This chapter presents the fundamental principles for modeling and controlling quadcopters that will form the basis for future research and development in the field of drones. The problem is addressed on two fronts; first, the mathematical dynamic models are developed, and second, the trajectory of the quadcopter is stabilized and controlled. IMUs (Inertial Measurement Units) consist of accelerometers and gyroscopes and constitute the core of the system. In order to fly the quadcopter in six directions, it is necessary to determine the orientation of the system and control the speed of four BLDC motors. A Matlab/Simulink analysis of the quadcopter is performed. A self-tuning fuzzy-PI regulator is used to control the quadcopter’s pitch, roll, and yaw. It was evaluated whether the quadcopter controller was effective and efficient, and the desired outputs were discussed.

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References

  1. Abdelmaksoud SI, Mailah M, Abdallah AM (2020) Robust intelligent self-tuning active force control of a quadrotor with improved body jerk performance. IEEE Access 8:150,037–150,050

    Google Scholar 

  2. Abdelmalek S, Azar AT, Dib D (2018) A novel actuator fault-tolerant control strategy of DFIG-based wind turbines using Takagi-Sugeno multiple models. Int J Control Autom Syst 16(3):1415–1424

    Article  Google Scholar 

  3. Adepoju O (2022) Drone/unmanned aerial vehicles (UAVs) technology. In: Re-skilling human resources for construction 4.0. Springer, pp 65–89

    Google Scholar 

  4. Al-Mahturi A, Santoso F, Garratt MA, Anavatti SG (2021) Modeling and control of a quadrotor unmanned aerial vehicle using type-2 fuzzy systems. In: Unmanned aerial systems. Elsevier, pp 25–46

    Google Scholar 

  5. Alaiwi Y, Mutlu A (2018) Modelling, simulation and implementation of autonomous unmanned quadrotor. Mach Technol Mater 12(8):320–325

    Google Scholar 

  6. Ammar HH, Azar AT (2020) Robust path tracking of mobile robot using fractional order PID controller. In: Hassanien AE, Azar AT, Gaber T, Bhatnagar R, Tolba MF (eds) The international conference on advanced machine learning technologies and applications (AMLTA2019). Advances in intelligent systems and computing, vol 921. Springer International Publishing, Cham, pp 370–381

    Google Scholar 

  7. Ammar HH, Azar AT, Tembi TD, Tony K, Sosa A (2018) Design and implementation of fuzzy PID controller into multi agent smart library system prototype. In: Hassanien AE, Tolba MF, Elhoseny M, Mostafa M (eds) The international conference on advanced machine learning technologies and applications (AMLTA2018). Advances in intelligent systems and computing, vol 723. Springer International Publishing, Cham, pp 127–137

    Google Scholar 

  8. Ananth DVN, Kumar LVS, Gorripotu TS, Azar AT (2021) Design of a fuzzy logic controller for short-term load forecasting with randomly varying load. Int J Sociotechnol Knowl Dev (IJSKD) 13(4):32–49

    Article  Google Scholar 

  9. Avant T, Lee U, Katona B, Morgansen K (2018) Dynamics, hover configurations, and rotor failure restabilization of a morphing quadrotor. In: 2018 Annual American control conference (ACC). IEEE, pp 4855–4862

    Google Scholar 

  10. Azar AT, Serrano FE (2014) Robust IMC-PID tuning for cascade control systems with gain and phase margin specifications. Neural Comput Appl 25(5):983–995

    Article  Google Scholar 

  11. Banu PN, Azar AT, Inbarani HH (2017) Fuzzy firefly clustering for tumour and cancer analysis. Int J Modell Identif Control 27(2):92–103. https://www.inderscienceonline.com/doi/pdf/10.1504/IJMIC.2017.082941

  12. Barakat MH, Azar AT, Ammar HH (2020) Agricultural service mobile robot modeling and control using artificial fuzzy logic and machine vision. In: Hassanien AE, Azar AT, Gaber T, Bhatnagar R, Tolba MF (eds) The international conference on advanced machine learning technologies and applications (AMLTA2019). Advances in intelligent systems and computing, vol 921. Springer International Publishing, Cham, pp 453–465

    Google Scholar 

  13. Boursianis AD, Papadopoulou MS, Diamantoulakis P, Liopa-Tsakalidi A, Barouchas P, Salahas G, Karagiannidis G, Wan S, Goudos SK (2020) Internet of things (IoT) and agricultural unmanned aerial vehicles (UAVs) in smart farming: a comprehensive review. Internet of Things, p 100187

    Google Scholar 

  14. Çetin E, Cano A, Deransy R, Tres S, Barrado C (2022) Implementing mitigations for improving societal acceptance of urban air mobility. Drones 6(2):28

    Article  Google Scholar 

  15. Chen F, Lei W, Zhang K, Tao G, Jiang B (2016) A novel nonlinear resilient control for a quadrotor UAV via backstepping control and nonlinear disturbance observer. Nonlinear Dyn 85(2):1281–1295

    Article  MATH  Google Scholar 

  16. Christensen H, Amato N, Yanco H, Mataric M, Choset H, Drobnis A, Goldberg K, Grizzle J, Hager G, Hollerbach J et al (2021) A roadmap for US robotics–from internet to robotics 2020 edition. Now Publishers

    Google Scholar 

  17. Coelho MS et al (2019) Hybrid PI controller constructed with paraconsistent annotated logic. Control Eng Pract 84:112–124

    Article  Google Scholar 

  18. Dasgupta R (2018) Adaptive attitude tracking of a quad-rotorcraft using nonlinear control hierarchy. In: 2018 IEEE recent advances in intelligent computational systems (RAICS). IEEE, pp 177–181

    Google Scholar 

  19. Dirican C (2015) The impacts of robotics, artificial intelligence on business and economics. Procedia Soc Behav Sci 195:564–573

    Article  Google Scholar 

  20. Emary E, Zawbaa HM, Hassanien AE, Schaefer G, Azar AT (2014) Retinal vessel segmentation based on possibilistic fuzzy c-means clustering optimised with cuckoo search. In: 2014 international joint conference on neural networks (IJCNN). IEEE, pp 1792–1796

    Google Scholar 

  21. Emran BJ, Najjaran H (2018) A review of quadrotor: an underactuated mechanical system. Annu Rev Control 46:165–180

    Article  MathSciNet  Google Scholar 

  22. Ennima S, Bourekkadi S, Ourdi A, Elgharad A (2021) Innovation attitude control of a hexacopter platform based on fractional control laws and comparison with the PID and LQR control methods. J Theoret Appl Inf Technol 99(9)

    Google Scholar 

  23. Fadel MZ et al (2019) Modeling, simulation and control of a fly-by-wire flight control system using classical PID and modified PI-D controllers. J Eur Syst Autom 52(3):267–276

    Google Scholar 

  24. Fekik A, Denoun H, Azar AT, Koubaa A, Kamal NA, Zaouia M, Hamida ML, Yassa N (2020) Adapted fuzzy fractional order proportional-integral controller for DC motor. In: 2020 first international conference of smart systems and emerging technologies (SMARTTECH), pp 1–6. https://doi.org/10.1109/SMART-TECH49988.2020.00019

  25. Fekik A, Hamida ML, Houassine H et al (2022) Observability of speed DC motor with self-tuning fuzzy-fractional-order controller. In: Fractional-order design. Academic Press, pp 157–179

    Google Scholar 

  26. Fekik A et al (2020) Adapted fuzzy fractional order proportional-integral controller for DC motor. In: 2020 first international conference of smart systems and emerging technologies (SMARTTECH). IEEE, pp 1–6

    Google Scholar 

  27. García J, Molina JM, Trincado J (2020) Real evaluation for designing sensor fusion in UAV platforms. Inf Fusion 63:136–152

    Article  Google Scholar 

  28. Ghoudelbourk S, Azar AT, Dib D (2021) Three-level (NPC) shunt active power filter based on fuzzy logic and fractional-order PI controller. Int J Autom Control 15(2):149–169

    Article  Google Scholar 

  29. Giordan D, Adams MS, Aicardi I, Alicandro M, Allasia P, Baldo M, De Berardinis P, Dominici D, Godone D, Hobbs P et al (2020) The use of unmanned aerial vehicles (UAVs) for engineering geology applications. Bull Eng Geol Env 79(7):3437–3481

    Article  Google Scholar 

  30. González-Jorge H, Martínez-Sánchez J, Bueno M et al (2017) Unmanned aerial systems for civil applications: a review. Drones 1(1):2

    Article  Google Scholar 

  31. Gorripotu TS, Samalla H, Jagan Mohana Rao C, Azar AT, Pelusi D (2019) TLBO algorithm optimized fractional-order PID controller for AGC of interconnected power system. In: Nayak J, Abraham A, Krishna BM, Chandra Sekhar GT, Das AK (eds) Soft computing in data analytics. Springer, Singapore, pp 847–855

    Chapter  Google Scholar 

  32. Hoffmann G, Huang H, Waslander S, Tomlin C (2007) Quadrotor helicopter flight dynamics and control: theory and experiment. In: AIAA guidance, navigation and control conference and exhibit, p 6461

    Google Scholar 

  33. Hua H, Fang Y, Zhang X, Lu B (2020) A novel robust observer-based nonlinear trajectory tracking control strategy for quadrotors. IEEE Trans Control Syst Technol 29(5):1952–1963

    Article  Google Scholar 

  34. Huang H, Hoffmann GM, Waslander SL, Tomlin CJ (2009) Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering. In: 2009 IEEE international conference on robotics and automation. IEEE, pp 3277–3282

    Google Scholar 

  35. Humaidi AJ, Najem HT, Al-Dujaili AQ, Pereira DA, Ibraheem IK, Azar AT (2021) Social spider optimization algorithm for tuning parameters in PD-like interval type-2 fuzzy logic controller applied to a parallel robot. Meas Control 54(3–4):303–323

    Article  Google Scholar 

  36. Ibraheem GAR, Azar AT, Ibraheem IK, Humaidi AJ (2020) A novel design of a neural network-based fractional PID controller for mobile robots using hybridized fruit fly and particle swarm optimization. Complexity 2020:1–18

    Article  Google Scholar 

  37. Johnson MH, Michael A et al (2005) PID control

    Google Scholar 

  38. Jung D, Tsiotras P (2007) Modeling and hardware-in-the-loop simulation for a small unmanned aerial vehicle. In: AIAA infotech@ aerospace 2007 conference and exhibit, p 2768

    Google Scholar 

  39. Kahouadji M, Mokhtari MR, Choukchou-Braham A, Cherki B (2020) Real-time attitude control of 3 DOF quadrotor UAV using modified super twisting algorithm. J Franklin Inst 357(5):2681–2695

    Article  MathSciNet  MATH  Google Scholar 

  40. Kandeel HM et al (2022) Modeling and control of x-shape quadcopter. IOSR J Mech Civil Eng (IOSR-JMCE) 19(1):46–57

    Google Scholar 

  41. Khan NA, Jhanjhi N, Brohi SN, Usmani RSA, Nayyar A (2020) Smart traffic monitoring system using unmanned aerial vehicles (UAVs). Comput Commun 157:434–443

    Article  Google Scholar 

  42. Khettab K, Bensafia Y, Bourouba B, Azar AT (2018) Enhanced fractional order indirect fuzzy adaptive synchronization of uncertain fractional chaotic systems based on the variable structure control: Robust h\(\infty \) design approach. In: Azar AT, Radwan AG, Vaidyanathan S (eds) Mathematical techniques of fractional order systems. Advances in nonlinear dynamics and chaos (ANDC). Elsevier, pp 597–624

    Google Scholar 

  43. Koubâa A, Azar AT (2021) Unmanned aerial systems: theoretical foundation and applications. Academic Press

    Google Scholar 

  44. Kumar J, Azar AT, Kumar V, Rana KPS (2018) Design of fractional order fuzzy sliding mode controller for nonlinear complex systems. In: Azar AT, Radwan AG, Vaidyanathan S (eds) Mathematical techniques of fractional order systems. Advances in nonlinear dynamics and chaos (ANDC). Elsevier, pp 249–282

    Google Scholar 

  45. Kumar KS, Rasheed M, Kumar RMM (2014) Design and implementation of fuzzy logic controller for quad rotor UAV. In: 2nd international conference on research in science, engineering and technology (ICRSET’2014). Dubai, pp 114–120

    Google Scholar 

  46. Maddikunta PKR, Hakak S, Alazab M, Bhattacharya S, Gadekallu TR, Khan WZ, Pham QV (2021) Unmanned aerial vehicles in smart agriculture: applications, requirements, and challenges. IEEE Sens J 21(16):17,608–17,619

    Google Scholar 

  47. Malpica C, Withrow-Maser S (2020) Handling qualities analysis of blade pitch and rotor speed controlled eVTOL quadrotor concepts for urban air mobility. In: VFS international powered lift conference, pp 21–23

    Google Scholar 

  48. Meghni B, Dib D, Azar AT (2017) A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage. Neural Comput Appl 28(6):1417–1434

    Article  Google Scholar 

  49. Meghni B, Dib D, Azar AT, Saadoun A (2018) Effective supervisory controller to extend optimal energy management in hybrid wind turbine under energy and reliability constraints. Int J Dyn Control 6(1):369–383

    Article  MathSciNet  Google Scholar 

  50. Mohammadi Daniali H (2020) Fast nonlinear model predictive control of quadrotors: design and experiments. Master’s thesis, University of Waterloo

    Google Scholar 

  51. Najm AA, Azar AT, Ibraheem IK, Humaidi AJ (2021) A nonlinear PID controller design for 6-DOF unmanned aerial vehicles. In: Koubaa A, Azar AT (eds) Unmanned aerial systems. Advances in nonlinear dynamics and chaos (ANDC). Academic Press, pp 315–343

    Google Scholar 

  52. Nex F, Remondino F (2014) UAV for 3D mapping applications: a review. Appl Geomat 6(1):1–15

    Article  Google Scholar 

  53. Nguyen NP, Mung NX, Thanh HLNN, Huynh TT, Lam NT, Hong SK (2021) Adaptive sliding mode control for attitude and altitude system of a quadcopter UAV via neural network. IEEE Access 9:40,076–40,085

    Google Scholar 

  54. Okyere E, Bousbaine A, Poyi GT, Joseph AK, Andrade JM (2019) LQR controller design for quad-rotor helicopters. J Eng 17:4003–4007

    Article  Google Scholar 

  55. Pilla R, Azar AT, Gorripotu TS (2019) Impact of flexible AC transmission system devices on automatic generation control with a metaheuristic based fuzzy PID controller. Energies 12(21):4193

    Article  Google Scholar 

  56. Pilla R, Botcha N, Gorripotu TS, Azar AT (2020) Fuzzy PID controller for automatic generation control of interconnected power system tuned by glow-worm swarm optimization. In: Nayak J, Balas VE, Favorskaya MN, Choudhury BB, Rao SKM, Naik B (eds) Applications of robotics in industry using advanced mechanisms. Springer International Publishing, Cham, pp 140–149

    Chapter  Google Scholar 

  57. Pilla R, Gorripotu TS, Azar AT (2021) Design and analysis of search group algorithm-based PD-PID controller plus redox flow battery for automatic generation control problem. Int J Comput Appl Technol 66(1):19–35

    Article  Google Scholar 

  58. Pintea CM, Matei O, Ramadan RA, Pavone M, Niazi M, Azar AT (2018) A fuzzy approach of sensitivity for multiple colonies on ant colony optimization. In: Balas VE, Jain LC, Balas MM (eds) Soft computing applications. Springer International Publishing, Cham, pp 87–95

    Chapter  Google Scholar 

  59. Rana K, Kumar V, Sehgal N, George S, Azar AT (2021) Efficient maximum power point tracking in fuel cell using the fractional-order PID controller. In: Azar AT, Kamal NA (eds) Renewable energy systems. Advances in nonlinear dynamics and chaos (ANDC). Academic Press, pp 111–132

    Google Scholar 

  60. Saidi SM, Mellah R, Fekik A, Azar AT (2022) Real-time fuzzy-PID for mobile robot control and vision-based obstacle avoidance. Int J Serv Sci Manag Eng Technol 13(1):1–32

    Google Scholar 

  61. Sallam OK, Azar AT, Guaily A, Ammar HH (2020) Tuning of PID controller using particle swarm optimization for cross flow heat exchanger based on CFD system identification. In: Hassanien AE, Shaalan K, Tolba MF (eds) Proceedings of the international conference on advanced intelligent systems and informatics 2019. Advances in intelligent systems and computing, vol 1058. Springer International Publishing, Cham, pp 300–312

    Google Scholar 

  62. Samanta S, Mukherjee A, Ashour AS, Dey N, Tavares JMRS, Abdessalem Karâa WB, Taiar R, Azar AT, Hassanien AE (2018) Log transform based optimal image enhancement using firefly algorithm for autonomous mini unmanned aerial vehicle: an application of aerial photography. Int J Image Graph 18(04):1850019. https://doi.org/10.1142/S0219467818500195

    Article  Google Scholar 

  63. Schneier M, Schneier M, Bostelman R (2015) Literature review of mobile robots for manufacturing. US Department of Commerce, National Institute of Standards and Technology

    Google Scholar 

  64. Shakhatreh H, Sawalmeh AH, Al-Fuqaha A, Dou Z, Almaita E, Khalil I, Othman NS, Khreishah A, Guizani M (2019) Unmanned aerial vehicles (UAVs): a survey on civil applications and key research challenges. IEEE Access 7:48,572–48,634

    Google Scholar 

  65. Shalaby R, Ammar HH, Azar AT, Mahmoud M (2021) Optimal fractional-order fuzzy-MPPT for solar water pumping system. J Intell Fuzzy Syst 40(1):(1):1175–1190

    Google Scholar 

  66. Soliman M, Azar AT, Saleh MA, Ammar HH (2020) Path planning control for 3-omni fighting robot using PID and fuzzy logic controller. In: Hassanien AE, Azar AT, Gaber T, Bhatnagar R, Tolba MF (eds) The international conference on advanced machine learning technologies and applications (AMLTA2019). Springer International Publishing, Cham, pp 442–452

    Chapter  Google Scholar 

  67. Sun X, Wandelt S, Zhang A (2021) Technological and educational challenges towards pandemic-resilient aviation. Transp Policy 114:104–115

    Article  Google Scholar 

  68. Thu KM, Gavrilov A (2017) Designing and modeling of quadcopter control system using L1 adaptive control. Procedia Comput Sci 103:528–535

    Article  Google Scholar 

  69. Vaidyanathan S, Azar AT (2016) Takagi-Sugeno fuzzy logic controller for Liu-Chen four-scroll chaotic system. Int J Intell Eng Inf 4(2):135–150

    Google Scholar 

  70. Velusamy P, Rajendran S, Mahendran RK, Naseer S, Shafiq M, Choi JG (2022) Unmanned aerial vehicles (UAV) in precision agriculture: applications and challenges. Energies 15(1):217

    Article  Google Scholar 

  71. Vidulich MA, Tsang PS (2019) Improving aviation performance through applying engineering psychology. Advances in aviation psychology, vol 3. CRC Press

    Google Scholar 

  72. Wakitani S et al (2019) Design and application of a database-driven PID controller with data-driven updating algorithm. Ind Eng Chem Res 58(26):11,419–11,429

    Google Scholar 

  73. Xie W, Cabecinhas D, Cunha R, Silvestre C (2021) Adaptive backstepping control of a quadcopter with uncertain vehicle mass, moment of inertia, and disturbances. IEEE Trans Industr Electron 69(1):549–559

    Article  Google Scholar 

  74. Yang T, Li P, Zhang H, Li J, Li Z (2018) Monocular vision slam-based UAV autonomous landing in emergencies and unknown environments. Electronics 7(5):73

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank Prince Sultan University, Riyadh, Saudi Arabia for supporting this work. Special acknowledgement to Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh, Saudi Arabia.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, University Akli Mohand Oulhadj-Bouria, Rue Drissi Yahia Bouira, 10000, Algeria

    Arezki Fekik

  2. Electrical Engineering Advanced Technology Laboratory (LATAGE), Mouloud Mammeri University, Tizi Ouzou, Algeria

    Arezki Fekik, Mohamed Lamine Hamida & Hakim Denoun

  3. College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Ahmad Taher Azar

  4. Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh, Saudi Arabia

    Ahmad Taher Azar

  5. Faculty of Computers and Artificial Intelligence, Benha University, Banha, Egypt

    Ahmad Taher Azar

  6. Department of Electrical Engineering L2CSP Laboratory Mouloud Mammeri University, 15000, Tizi-Ouzou, Algeria

    Sabrina Mohandsaidi

  7. University of Derby, Derby, UK

    Amar Bousbaine

  8. Faculty of Engineering, Cairo University, Giza, Egypt

    Nashwa Ahmad Kamal

  9. Department of Computer Techniques Engineering, Dijlah University College, Baghdad, 10001, Iraq

    Ibraheem Kasim Ibraheem

  10. Control and Systems Engineering Department, University of Technology, Baghdad, Iraq

    Amjad J. Humaidi

  11. Department of Computer Science, Edge Hill University, Ormskirk, UK

    Ammar K. Al Mhdawi

  12. General Motors Canada, 500 Wentworth St W, Oshawa, ON, L1J 6J2, Canada

    Alaa Khamis

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  1. Arezki Fekik
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Correspondence to Arezki Fekik .

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Editors and Affiliations

  1. Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt

    Ahmad Taher Azar

  2. Electrical Engineering Department, University of Baghdad, College of Engineering, Baghdad, Iraq

    Ibraheem Kasim Ibraheem

  3. University of Technology, Baghdad, Iraq

    Amjad Jaleel Humaidi

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Fekik, A. et al. (2023). Modeling and Simulation of Quadcopter Using Self-tuning Fuzzy-PI Controller. In: Azar, A.T., Kasim Ibraheem, I., Jaleel Humaidi, A. (eds) Mobile Robot: Motion Control and Path Planning. Studies in Computational Intelligence, vol 1090. Springer, Cham. https://doi.org/10.1007/978-3-031-26564-8_8

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