Simulation and implementation of alternative attitude control algorithms for a micro multirotor flying platform

• Autorzy: Gąsior P. , Gąsior M.
• Języki publikacji: EN

Abstrakty

EN

The most popular control algorithm in attitude stabilization of multirotor aerial vehicles is a PID controller. It is used so frequently because of low computational requirements and simplicity of implementation and tuning. However, there are many other control algorithms suitable for this task, for example fuzzy logic or neural networks controllers. These algorithms are more complex than PID, but with appropriate knowledge and hardware it is possible to implement them in the on-board controller. This paper presents the comparison of the mentioned algorithms during simulation experiments. The construction process of a micro multirotor flying platform NeuroQuad and the implementation of the tested algorithms on this platform are described.

Słowa kluczowe

EN

quadrotor; control; fuzzy logic; ANN; PID; NeuroQuad

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2015
• Tom: Vol. 61, No. 7
• Strony: 346--348
• Opis fizyczny: Bibliogr. 7 poz., rys., tab.

Twórcy

autor

Gąsior P.

• Institute of Control and Information Engineering, Poznan University of Technology, 3A Piotrowo St., 60-965 Poznan, Poland

autor

Gąsior M.

• Institute of Control and Information Engineering, Poznan University of Technology, 3A Piotrowo St., 60-965 Poznan, Poland

Bibliografia

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• [2] Rezazadeh S., Ardestani M.A., Sadeghi P. S.: Optimal attitude control of a quadrotor UAV using Adaptive Neuro-Fuzzy Inference System (ANFIS). Control, Instrumentation, and Automation (ICCIA), pp. 219-223, 2013.
• [3] Mahony R., Kumar V., Corke P.: Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Quadrotor. Robotics & Automation Magazine, IEEE, vol. 19, pp. 20-32, 2012.
• [4] Pounds P.: Design, construction and control of a large quadrotor micro air vehicle. Thesis, 2007.
• [5] Corke P.: Robotics, Vision and Control. Springer Tracts in Advanced Robotics, vol. 73, 2011.
• [6] Mahony R., Hamel T., Pflimlin J.: Complementary filter design on the special orthogonal group SO(3). Decision and Control, European Control Conference. CDC-ECC '05. 44th IEEE Conference on, pp.1,6, 1477-1484, Dec. 2005.
• [7] Gąsior P., Gardecki S., Gośliński J., Giernacki W.: Estimation of Altitude and Vertical Velocity for Multirotor Aerial Vehicle Using Kalman Filter. Advances in Intelligent Systems and Computing, vol. 267, 377-385, 2014.