Wind-gust Compensation Algorithm based on High-gain Residual Observer to Control a Quadrotor Aircraft: Real-time Verification Task at Fixed Point

  • Abraham Efraim Rodríguez-Mata
  • Ivan González-Hernández
  • Jesus Gabriel Rangel-Peraza
  • Sergio Salazar
  • Rogelio Lozano Leal
Regular Paper Robot and Applications
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Abstract

Wind is considered a strong disturbance for quadrotor aircrafts (UAV) when an outdoor task at a fixed point is carried out. The effect of wind produces a distortion on the attitude of the vehicle which is reflected on undesired longitudinal movements. This paper addresses a real-time implementation and design of a robust embedded control-observer based on a type high-gain observer algorithm for on-line estimation and compensation of external disturbances produced by wind gusts on an autonomous quadrotor aircraft. A real-time experimental implementation of embedded Residual High Gain algorithm control is proposed in order to eliminate the effects of real perturbations in the hover position of the UAV. A Lyapunov function was used to practical stability analysis the system. Also numerical simulations were carried out to estimate wind behavior by the use of Drydel mathematical wind model. The main contribution of this work is the implementation of a Residual High Gain Observer in an outdoor real-time experiment in presence of real wind gusts perturbations. The proposed embedded algorithm control improves the stabilization of an UAV in the presence of real wind gusts with average of 8 m/s. The proposed algorithm improved the UAV behavior as shown by the GPS position experimental results, decreasing the wind effect on the translational movement of the aircraft.

Keywords

Embedded control system high gain observer algorithm quadrotor aircraft robust attitude control wind gust rejection 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Abraham Efraim Rodríguez-Mata
    • 1
    • 2
  • Ivan González-Hernández
    • 3
  • Jesus Gabriel Rangel-Peraza
    • 1
  • Sergio Salazar
    • 3
  • Rogelio Lozano Leal
    • 3
  1. 1.Tecnológico Nacional de MéxicoInstituto Tecnológico de CuliacánSinaloaMéxico
  2. 2.CONACyTMexico CityMéxico
  3. 3.UMI-LAFMIA, CINVESTAV, Mexico and Laboratorio NacionalSinaloaMéxico

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