Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Study of Sensor Fusion for Attitude Control of a Quad-rotor

쿼드로터 자세제어를 위한 센서융합 연구

  • Yu, Dong-Hyeon (School of Department of Electronic Engineering, Chon-buk National University) ;
  • Lim, Dae Young (School of Department of Electronic Engineering, Chon-buk National University) ;
  • Sel, Nam O (School of Department of Electronic & Electronic Engineering, Seonam University) ;
  • Park, Jong Ho (School of Department of Electronic & Electronic Engineering, Seonam University) ;
  • Chong, Kil to (School of Department of Electronic Engineering, Chon-buk National University)
  • 유동현 (전북대학교 전자공학부) ;
  • 임대영 (전북대학교 전자공학부) ;
  • 설남오 (서남대학교 전기전자공학과) ;
  • 박종호 (서남대학교 전기전자공학과) ;
  • 정길도 (전북대학교 전자공학부)
  • Received : 2014.11.24
  • Accepted : 2015.01.30
  • Published : 2015.05.01
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Abstract

We presented a quad-rotor controlling algorithm design by using sensor fusion in this paper. The controller design technique was performed by a PD controller with a Kalman filter and compensation algorithm for increasing the stability and reliability of the quad-rotor attitude. In this paper, we propose an attitude estimation algorithm for quad-rotor based sensor fusion by using the Kalman filter. For this reason, firstly, we studied the platform configuration and principle of the quad-rotor. Secondly, the bias errors of a gyro sensor, acceleration and geomagnetic sensor are compensated. The measured values of each sensor are then fused via a Kalman filter. Finally, the performance of the proposed algorithm is evaluated through experimental data of attitude estimation. As a result, the proposed sensor fusion algorithm showed superior attitude estimation performance, and also proved that robust attitude estimation is possible even in disturbance.

Keywords

References

  1. Vicente martinez martinez, "Modelling of the flight dynamics of a qaudrotor helicopter," Cranfield, pp. 36-45, Sep. 2007.
  2. J. G. Lim and S. Jeong, "Design and experimental studies of a disturbance observer for attitude control of a quad-rotor system," Journal Institute of Control, Robotics and Systems (in Korean), vol. 19, no. 11, pp. 1004-10010, Nov. 2013. https://doi.org/10.5302/J.ICROS.2013.13.1890
  3. M. D. Schmidt, "Simulation and control of a Quadrotor unmanned aerial vehicle," University of Kentucky, pp. 1-26, Apr. 2011.
  4. S.-H. Choi, Y.-K. Kim, Y.-S. Hwang, H.-W. Kim, and J.-M. Lee, "EKF base outdoor positioning system using multiple GPS receivers," Journal of Korea Robotics Society, vol. 8, no. 2, pp. 129-135, Mar. 2013. https://doi.org/10.7746/jkros.2013.8.2.129
  5. R. W. Beard, "Quadrotor dynamics and control," Brigham Young University, Oct. 2008.
  6. P. Martin and E. Salaiin, "The true role of accelerometer feedback in quadrotor control," hal-00422423, version. 1-6, Oct. 2009.
  7. J.-S. Kim, "The simulator for control of quadcopter using sensor combination," Dong a University, pp. 23-25, 2011.
  8. D. K. Nam, J. Y. Park, H. W. Park, and D. Y. Kim, "Some observations on drift-reduction methods for low-cost gyro sensors," Proc. of KIIS Fall Conference 2010, vol. 20, no. 2, 2010.
  9. J. Borenstein and L. Ojeda, "Heuristic reduction of gyro drift in gyro-based vehicle tracking," Journal of Navigation, vol. 62, no. 1, pp. 41-58, Dec. 2008. https://doi.org/10.1017/S0373463308005043
  10. S. Haykin, "Kalman filtering and neural networks," Awiley-Interscience Publication, pp. 16-53, 2001.
  11. J. Y. Choe and S. G. Kim, "Study on the localization improvement of the dead reckoning using the INS calibrated by the fusion aensor network information," Journal Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 8, pp. 744-749, Oct. 2012. https://doi.org/10.5302/J.ICROS.2012.18.8.744

Cited by

  1. Geomagnetic Sensor Compensation and Sensor Fusion for Quadrotor Heading Direction Control vol.53, pp.7, 2016, https://doi.org/10.5573/ieie.2016.53.7.095