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Accurate Modeling and Robust Hovering Control for a Quad–rotor VTOL Aircraft

  • Kim, Jinhyun1
  • Kang, Min-Sung2
  • Park, Sangdeok3
  • 1 Seoul National University of Technology, Department of Mechanical Engineering, Seoul, South Korea , Seoul (South Korea)
  • 2 Hanyang University, Department of Mechatronics Engineering, Ansan, South Korea , Ansan (South Korea)
  • 3 Korea Institute of Industrial Technology, Division of Applied Robot Technology, Ansan, South Korea , Ansan (South Korea)
Published Article
Journal of Intelligent & Robotic Systems
Publication Date
Sep 17, 2009
DOI: 10.1007/s10846-009-9369-z
Springer Nature


Quad-robot type (QRT) unmanned aerial vehicles (UAVs) have been developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV is equipped with four propellers driven by each electric motor, an embedded controller, an Inertial Navigation System (INS) using three rate gyros and accelerometers, a CCD (Charge Coupled Device) camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. Accurate modeling and robust flight control of QRT UAVs are mainly discussed in this work. Rigorous dynamic model of a QRT UAV is obtained both in the reference and body frame coordinate systems. A disturbance observer (DOB) based controller using the derived dynamic models is also proposed for robust hovering control. The control input induced by DOB is helpful to use simple equations of motion satisfying accurately derived dynamics. The developed hovering robot shows stable flying performances under the adoption of DOB and the vision based localization method. Although a model is incorrect, DOB method can design a controller by regarding the inaccurate part of the model and sensor noises as disturbances. The UAV can also avoid obstacles using eight IR (Infrared) and four ultrasonic range sensors. This kind of micro UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment. The experimental results show the performance of the proposed control algorithm.

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