On Using Fuzzy Logic to Control a Simulated Hexacopter Carrying an Attached Pendulum

  • Emanoel KosloskyEmail author
  • Marco A. Wehrmeister
  • João A. Fabro
  • André S. de Oliveira
Part of the Studies in Computational Intelligence book series (SCI, volume 664)


Fuzzy logic is used in many applications from industrial process control to automotive applications, including consumers trend forecast, aircraft maneuvering control and others. Considering the increased interest in using of multi-rotor aircrafts (usually called drones) for many kinds of applications, it is important to study new methods to improve multi-rotor maneuverability while controlling its stability in a proper way. Controlling the flight of multi-rotors, specially those equipped six rotors, is not a trivial task. When considering the design of such a control systems, traditional approaches such as PD/PID are very difficult to design, in spite of being easily implementable.


Target Position Pitch Angle Unman Aerial Vehicle Fuzzy Controller Vertical Speed 
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  1. 1.
    Ahmed OA, Latief M, Ali MA, Akmeliawati R (2015) Stabilization and control of autonomous hexacopter via visual-servoing and cascaded-proportional and derivative (PD) controllers. 2015 6th international conference on automation, robotics and applications (ICARA), pp 542–549. IEEEGoogle Scholar
  2. 2.
    Alaimo A, Artale V, Milazzo CLR, Ricciardello A (2014) PID controller applied to hexacopter flight. J Intell Robot Syst 73:261–270CrossRefGoogle Scholar
  3. 3.
    Bacik J, Perdukova D, Fedor P (2015) Design of fuzzy controller for hexacopter position control. artificial intelligence perspectives and applications. Advances in intelligent systems and computing. Springer International Publishing, Berlin, pp 192–202Google Scholar
  4. 4.
    Bipin K, Duggal V, Madhava K (2015) Autonomous navigation of generic monocular quadcopter in natural environment. Autonomous navigation of generic monocular quadcopter in natural environment, pp 1063–1070. IEEEGoogle Scholar
  5. 5.
    Collotta M, Pau G, Caponetto R (2014) A real-time system based on a neural network model to control hexacopter trajectories. 2014 international symposium on power electronics, electrical drives, automation and motion (SPEEDAM)Google Scholar
  6. 6.
    Genetic algorithm applied to the stabilization control of a hexarotor (2015) Genetic algorithm applied to the stabilization control of a hexarotor. In: Proceedings of the international conference on numerical analysis and applied mathematics, vol 1648Google Scholar
  7. 7.
    Haque Md R, Muhammad M, Swarnaker D, Arifuzzaman M (2014) Autonomous Quadcopter for product home delivery. 2014 international conference on electrical engineering and information & communication technology (ICEEICT), pp 1–5. IEEEGoogle Scholar
  8. 8.
    Lee EA, Seshia SA (2015) Introduction to embedded systems – a cyber-physical systems approach, 2nd edn. Springer, New York, Chapters 1–3
  9. 9.
    Leishman R, Macdonald J, McLain T, Beard R (2012) Relative navigation and control of a hexacopter. Autonomous Quadcopter for product home delivery. 2012 IEEE international conference on robotics and automation (ICRA)Google Scholar
  10. 10.
    Ma sum MA, Jati G, Arrofi MK, Wibowo A, Mursanto P, Jatmiko W (2013) Autonomous quadcopter swarm robots for object localization and tracking. 2013 international symposium on micro-nanomechatronics and human science (MHS)Google Scholar
  11. 11.
    Ołdziej D, Gosiewski Z (2013) Modelling of Dynamic and control of six-rotor autonomous unmanned aerial vehicle. solid state phenomena. Trans Tech Publ, pp 220–225Google Scholar
  12. 12.
    Passino KM, Yurkvich S (1998) Fuzzy control, 1.2–conventional control system design. Addison-wesley, Boston Subsection 2.2Google Scholar
  13. 13.
    Rohmer E, Singh SPN, Freese M (2013) V-REP: A versatile and scalable robot simulation framework. 2013 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 1321–1326. IEEEGoogle Scholar
  14. 14.
    Salih AL, Moghavvemi M, Mohamed HAF, Gaeid KS (2010) Scientific Research and Essays. Flight PID controller design for a UAV quadrotor. Academic Journals, DenmarkGoogle Scholar
  15. 15.
    Siegwart R, Nourbakhsh IR, Scaramuzza D (2011) Introduction to autonomous mobile robots. MIT press, CambridgeGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Emanoel Koslosky
    • 1
    Email author
  • Marco A. Wehrmeister
    • 1
  • João A. Fabro
    • 1
  • André S. de Oliveira
    • 1
  1. 1.Federal University of Technology - Paraná (UTFPR)CuritibaBrazil

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