DOI QR코드

DOI QR Code

Attitude Control of Quad-rotor by Improving the Reliability of Multi-Sensor System

다종 센서 융합의 신뢰성 향상을 통한 쿼드로터 자세 제어

  • Yu, Dong Hyeon (School of Electronic Engineering, Chon-buk Nat'l Univ.) ;
  • Park, Jong Ho (Dept. of Electrical & Electronic Engineering, Seonam Univ.) ;
  • Ryu, Ji Hyoung (Electronics and Telecommunications Research Institute, ETRI) ;
  • Chong, Kil To (School of Electronic Engineering, Chon-buk Nat'l Univ.)
  • 유동현 (전북대학교 전자공학부) ;
  • 박종호 (서남대학교 전기전자공학과) ;
  • 류지형 (한국전자통신연구원 호남권연구센터) ;
  • 정길도 (전북대학교 전자공학부)
  • Received : 2014.10.13
  • Accepted : 2015.02.16
  • Published : 2015.05.01

Abstract

This paper presents the results of study for improving the reliability of quadrotor attitude control by applying a multi-sensor along with a data fusion algorithm. First, a mathematical model of the quadrotor dynamics was developed. Then, using the quadrotor mathematical model, simulations were performed using the improved reliability multi-sensor data as the inputs. From the simulation results, we designed a Gimbal-equipped quadrotor system. With the quadrotor in a hover state, we performed experiments according to the angle change of the user's specifications. We then calculated the attitude control data from the actual experimental data. Furthermore, with additional simulations, we verified the performance of the designed quadrotor attitude control system with multiple sensors.

Keywords

Attitude Control;Copter;Kalman Filter;PD Control;Quad-rotor;Sensor Fusion;Unmanned Aerial Vehicle

Acknowledgement

Supported by : 한국연구재단

References

  1. Byeon, S. M., Lee, K. M. and Yoon, S. H., 2013, "An Autonomous Navigation Algorithm for Quadcopter Using Multiple Seonsors," Korean Engineering-Art Institute Journal, Vol. 5, No. 1.
  2. Goel, R., Shah, S. M., Gupta, N. K. and Ananthkrishnan, N., 2009, "Modeling, Simulation and Flight Testing of an Autonomous Quadrotor," Proceedings of ICEAE 2009.
  3. Salazar-Cruz, S. and Lozano, R., 2005 "Stabilization and Nonlinear Control for a Novel Trirotor Mini-aircarft," 2005 IEEE International Conference on Robotics and Automation, pp.2612-2617.
  4. Kim, H., Jeong, S. H., Chong, K. T. and Lee, D. J., 2014, "Dynamic Modeling and Control Techniques for Multi-Rotor Flying Robots" Trans. Korean Soc. Mech. Eng. A, Vol. 38, No. 2, pp. 137-148. https://doi.org/10.3795/KSME-A.2014.38.2.137
  5. Yun, H. J., Choi, H. Y. and Lee, J. S., 2014, "CFD-based Thrust Analysis of Unmanned Aerial Vehicle in Hover Mode : Effects of Single Rotor Blade Shape," Trans. Korean Soc. Mech. Eng, A, Vol. 38, No. 5, pp. 513-520.
  6. Chowdhary, G. and Jategaonkar, R., 2006, "Aerodynamic Parameter Estimation rom Flight Data Applying Extended and Unscented Kalman Filter," DLR Institute for Flight System, Braunschweig, Germany, AIAA 2006-6146.
  7. Wan, E. A. and van der Merwe, R., 2000, "The Unscented Kalman Filter for Nonlinear Estimation" IEEE Symposium 2000.
  8. Abas, N., Legowo, A. and Akmeliawati, R., 2011, "Parameter Identification of and Autonomous Quadrotor," International Conference on Mechatronics (ICOM).
  9. Lee, K. U., Yun, Y. H., Chang, W., Park, B. J. and Choi, H. Y., 2011, "Modeling and Controller Design of Quadrotor UAV," KIEESummer Conference 2011.

Cited by

  1. Performance Enhancement of the Attitude Estimation using Small Quadrotor by Vision-based Marker Tracking vol.25, pp.5, 2015, https://doi.org/10.5391/JKIIS.2015.25.5.444
  2. 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