Research Article
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Year 2023, Volume: 9 Issue: 4, 1005 - 1019, 22.12.2023
https://doi.org/10.28979/jarnas.1318975

Abstract

References

  • Baldi, T.L., Farina, F., Garulli, A., Giannitrapani, A., and Prattichizzo, D. (2019). Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter. IEEE Sens. J., 20, 492–500. DOI: https://doi.org/10.1109/JSEN.2019.2940612
  • Beck, H. Lesueur, J., Charland-Arcand, G., Akhrif, O., Gagne, S., Gagnon F., and Couillard, D. (2016). Autonomous takeoff and landing of a quadcopter. International Conference on Unmanned Aircraft Systems (lCUAS), 475-484. DOI: https://doi.org/10.1109/ICUAS.2016.7502614
  • Benic, Z, Piljek, P., and Kotarski, D. (2016). Mathematical modelling of unmanned aerial vehicle with four rotors. Interdisciplinary Description of Complex Systems, 14(1), 88-100. DOI: http://dx.doi.org/10.7906/indecs.14.1.9
  • Bouktir, Y. Haddad, M., and Chettibi, T.(2008).Trajectory planning for a quad-rotor helicopter. 16th Mediterranean Conference on Control and Automation, 1258–1263. DOI: https://doi.org/10.1109/MED.2008.4602025
  • Buskey, G., Roberts, J., Corke, P., Ridley, P., and Wyeth, G. (2004) Sensing and control for a small-size helicopter. Experimental Robotics VIII: Springer Tracts in Advanced Robotics, 5. DOI: https://doi.org/10.1007/3-540-36268-1_43
  • Castillo, C. L., Moreno, W., and Valavanis, K. P., (2007). Unmanned helicopter waypoint trajectory tracking using model predictive control. Mediterranean Conference on Control and Automation. DOI: https://doi.org/10.1109/MED.2007.4433726
  • Chamseddine, A., Li, T., Zhang, Y., Rabbath, C.-A. and Theilliol, D. (2012). Flatness-based trajectory planning for a quad-rotor unmanned aerial vehicle test-bed considering actuator and system constraints. American Control Conference (ACC), 920–925. DOI: https://doi.org/10.1109/ACC.2012.6315362
  • Crasidis, J. L., Junkis, J. L. (2011) Optimal Estimation of Dynamic Systems Second Edition –CRC. De Marina, H. G., Pereda, F. J., Giron-Sierra, J. M. and Espinosa, F. (2012). UAV attitude estimation using unscented Kalman filter and triad. IEEE Transactions on Industrial Electronics, 59(11), 4465-4474. DOI: https://doi.org/10.1109/TIE.2011.2163913
  • Euston, M., Coote, P., Mahony, R., Kim J., and Hamel, T. (2008). A complementary filter for attitude estimation of a fixed-wing UAV. 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, France, 340-345. DOI: https://doi.org/10.1109/IROS.2008.4650766
  • Hall, J. K., Knoebel, N. B., and McLain, T. W. (2008). Quaternion attitude estimation for miniature air vehicles using a multiplicative extended Kalman filter. IEEE Position, Location and Navigation Symposium,1230- 1237. DOI: https://doi.org/10.1109/PLANS.2008.4570043
  • Hetenyi, D., Gatzy, M. and Blazovics, L. (2016). Sensor fusion with enhanced Kalman Filter for altitude control of quad-rotors. IEEE 11th International Symposium on Applied Computational intelligence and Informatics (SACI), 413-418. DOI: https://doi.org/10.1109/SACI.2016.7507412
  • Hoffmann, G., Waslander, S., and Tomlin, C. (2008). Quad-rotor helicopter trajectory tracking control. AIAA Guidance, Navigation and Control Conference and Exhibit, 1–14. DOI: https://doi.org/10.2514/6.2008-7410
  • Markley, F.L., Crassidis, J.L. (2014). Fundamentals of Spacecraft Attitude Determination and Control. Space Technology Library, 33. Springer, New York, NY. DOI: https://doi.org/10.1007/978-1-4939-0802-8 Mahony, R., Hamel T., and Ptlimlin, J.-M. (2008). Nonlinear complementary filters on the special orthogonal group. IEEE Trans. on Automatic Control, 53(5), 1203-1218. DOI: https://doi.org/10.1109/TAC.2008.923738
  • Pines D. J., Bohorquez F. (2012). Challenges Facing Future Micro-Air-Vehicle Development, Journal of Aircraft, 43(2):290-305. DOI: https://doi.org/10.2514/1.4922
  • Sebesta, K.-D., Boizot, N. (2014). A real-time adaptive high-gain EKF, Applied to a quadcopter inertial navigation system. IEEE Trans. on Industrial Electronics, 61(1), 495-503. DOI: https://doi.org/10.1109/TIE.2013.2253063
  • Shen, C., Zhang, Y., Guo, X., Chen, X., Cao, H., Tang, J., Li, J., Liu, J. (2020). Seamless GPS/inertial navigation system based on self-learning square-root cubature Kalman filter. IEEE Transactions on Industrial Electronics, 68(1), 499–508. DOI: https://doi.org/10.1109/TIE.2020.2967671
  • Suh, Y.S. (2020). Attitude Estimation Using Inertial and Magnetic Sensors Based on Hybrid Four-Parameter Complementary Filter. IEEE Trans. Instrum. Meas., 69, 5149–5156. DOI: https://doi.org/10.1109/TIM.2019.2950826
  • Usman, M. (2020) Quad-rotor Modelling and Control with MATLAB/Simulink Implementation, Thesis (B.S.), LAB University of Applied Sciences. Vik, B., Fossen, T. I. (2001). A nonlinear observer for GPS and INS integration. 40th IEEE Conference on Decision and Control, 2001. DOI: https://doi.org/10.1109/CDC.2001.980726
  • Wang, M., Yang, Y., Hatch, R.R., and Zhang, Y. (2004). Adaptive filter for a miniature mems-based attitude and heading reference system. Position Location and Navigation Symposium, 193–200, 26-29 April, 2004. DOI: https://doi.org/10.1109/plans.2004.1308993
  • Yang, Y., Long, P., Song, X., Pan, J., and Zhang, L. (2021). Optimization-Based Framework for Excavation Trajectory Generation. IEEE Robotics and Automation Letters, 6(2), April, 2021. DOI: https://doi.org/10.1109/LRA.2021.3058071
  • Yoon, J., Doh, J. (2022). Optimal PID control for hovering stabilization of quadcopter using long short term memory. Advanced Engineering Informatics, 53, 101679. DOI: https://doi.org/10.1016/j.aei.2022.101679
  • Zheng, L., Zhan, X., Zhang, X. (2020). Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera. Sensors, 20, 6752. DOI: https://doi.org/10.3390/s20236752
  • Zuo, Z. (2010). Trajectory tracking control design with command-filtered compensation for a quad-rotor, IET Control Theory Appl., 4, (11), 2343–2355. DOI: https://doi.org/10.1049/iet-cta.2009.0336

Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor

Year 2023, Volume: 9 Issue: 4, 1005 - 1019, 22.12.2023
https://doi.org/10.28979/jarnas.1318975

Abstract

Quad-rotor aircrafts are unmanned aerial vehicles that have gained significant popularity in recent years and have been developed for use in many areas. Such vehicles are capable of vertical take-off and landing and are used in various applications. To operate a quad-rotor aircraft efficiently and safely, fundamental issues such as mathematical modeling, control, and state estimation need to be studied. Mathematical modeling involves creating a holistic model of the various subsystems of the aircraft including aerody-namic, kinematic, dynamic and control systems. The control system is a mechanism used for the aircraft to perform the desired movements. State estimation techniques are used to obtain and predict information about the state of the aircraft. This study includes position control using a trajectory generation algorithm. Attitude estimation of the quad-rotor is improved with the Explicit Complementary Filter (ECF) and the state estimations is improved with the Extended Kalman Filter (EKF). Different from other studies, the results are obtained by feeding the model with a state estimation filter. The performances of the filters used for state estimation are compared.

References

  • Baldi, T.L., Farina, F., Garulli, A., Giannitrapani, A., and Prattichizzo, D. (2019). Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter. IEEE Sens. J., 20, 492–500. DOI: https://doi.org/10.1109/JSEN.2019.2940612
  • Beck, H. Lesueur, J., Charland-Arcand, G., Akhrif, O., Gagne, S., Gagnon F., and Couillard, D. (2016). Autonomous takeoff and landing of a quadcopter. International Conference on Unmanned Aircraft Systems (lCUAS), 475-484. DOI: https://doi.org/10.1109/ICUAS.2016.7502614
  • Benic, Z, Piljek, P., and Kotarski, D. (2016). Mathematical modelling of unmanned aerial vehicle with four rotors. Interdisciplinary Description of Complex Systems, 14(1), 88-100. DOI: http://dx.doi.org/10.7906/indecs.14.1.9
  • Bouktir, Y. Haddad, M., and Chettibi, T.(2008).Trajectory planning for a quad-rotor helicopter. 16th Mediterranean Conference on Control and Automation, 1258–1263. DOI: https://doi.org/10.1109/MED.2008.4602025
  • Buskey, G., Roberts, J., Corke, P., Ridley, P., and Wyeth, G. (2004) Sensing and control for a small-size helicopter. Experimental Robotics VIII: Springer Tracts in Advanced Robotics, 5. DOI: https://doi.org/10.1007/3-540-36268-1_43
  • Castillo, C. L., Moreno, W., and Valavanis, K. P., (2007). Unmanned helicopter waypoint trajectory tracking using model predictive control. Mediterranean Conference on Control and Automation. DOI: https://doi.org/10.1109/MED.2007.4433726
  • Chamseddine, A., Li, T., Zhang, Y., Rabbath, C.-A. and Theilliol, D. (2012). Flatness-based trajectory planning for a quad-rotor unmanned aerial vehicle test-bed considering actuator and system constraints. American Control Conference (ACC), 920–925. DOI: https://doi.org/10.1109/ACC.2012.6315362
  • Crasidis, J. L., Junkis, J. L. (2011) Optimal Estimation of Dynamic Systems Second Edition –CRC. De Marina, H. G., Pereda, F. J., Giron-Sierra, J. M. and Espinosa, F. (2012). UAV attitude estimation using unscented Kalman filter and triad. IEEE Transactions on Industrial Electronics, 59(11), 4465-4474. DOI: https://doi.org/10.1109/TIE.2011.2163913
  • Euston, M., Coote, P., Mahony, R., Kim J., and Hamel, T. (2008). A complementary filter for attitude estimation of a fixed-wing UAV. 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, France, 340-345. DOI: https://doi.org/10.1109/IROS.2008.4650766
  • Hall, J. K., Knoebel, N. B., and McLain, T. W. (2008). Quaternion attitude estimation for miniature air vehicles using a multiplicative extended Kalman filter. IEEE Position, Location and Navigation Symposium,1230- 1237. DOI: https://doi.org/10.1109/PLANS.2008.4570043
  • Hetenyi, D., Gatzy, M. and Blazovics, L. (2016). Sensor fusion with enhanced Kalman Filter for altitude control of quad-rotors. IEEE 11th International Symposium on Applied Computational intelligence and Informatics (SACI), 413-418. DOI: https://doi.org/10.1109/SACI.2016.7507412
  • Hoffmann, G., Waslander, S., and Tomlin, C. (2008). Quad-rotor helicopter trajectory tracking control. AIAA Guidance, Navigation and Control Conference and Exhibit, 1–14. DOI: https://doi.org/10.2514/6.2008-7410
  • Markley, F.L., Crassidis, J.L. (2014). Fundamentals of Spacecraft Attitude Determination and Control. Space Technology Library, 33. Springer, New York, NY. DOI: https://doi.org/10.1007/978-1-4939-0802-8 Mahony, R., Hamel T., and Ptlimlin, J.-M. (2008). Nonlinear complementary filters on the special orthogonal group. IEEE Trans. on Automatic Control, 53(5), 1203-1218. DOI: https://doi.org/10.1109/TAC.2008.923738
  • Pines D. J., Bohorquez F. (2012). Challenges Facing Future Micro-Air-Vehicle Development, Journal of Aircraft, 43(2):290-305. DOI: https://doi.org/10.2514/1.4922
  • Sebesta, K.-D., Boizot, N. (2014). A real-time adaptive high-gain EKF, Applied to a quadcopter inertial navigation system. IEEE Trans. on Industrial Electronics, 61(1), 495-503. DOI: https://doi.org/10.1109/TIE.2013.2253063
  • Shen, C., Zhang, Y., Guo, X., Chen, X., Cao, H., Tang, J., Li, J., Liu, J. (2020). Seamless GPS/inertial navigation system based on self-learning square-root cubature Kalman filter. IEEE Transactions on Industrial Electronics, 68(1), 499–508. DOI: https://doi.org/10.1109/TIE.2020.2967671
  • Suh, Y.S. (2020). Attitude Estimation Using Inertial and Magnetic Sensors Based on Hybrid Four-Parameter Complementary Filter. IEEE Trans. Instrum. Meas., 69, 5149–5156. DOI: https://doi.org/10.1109/TIM.2019.2950826
  • Usman, M. (2020) Quad-rotor Modelling and Control with MATLAB/Simulink Implementation, Thesis (B.S.), LAB University of Applied Sciences. Vik, B., Fossen, T. I. (2001). A nonlinear observer for GPS and INS integration. 40th IEEE Conference on Decision and Control, 2001. DOI: https://doi.org/10.1109/CDC.2001.980726
  • Wang, M., Yang, Y., Hatch, R.R., and Zhang, Y. (2004). Adaptive filter for a miniature mems-based attitude and heading reference system. Position Location and Navigation Symposium, 193–200, 26-29 April, 2004. DOI: https://doi.org/10.1109/plans.2004.1308993
  • Yang, Y., Long, P., Song, X., Pan, J., and Zhang, L. (2021). Optimization-Based Framework for Excavation Trajectory Generation. IEEE Robotics and Automation Letters, 6(2), April, 2021. DOI: https://doi.org/10.1109/LRA.2021.3058071
  • Yoon, J., Doh, J. (2022). Optimal PID control for hovering stabilization of quadcopter using long short term memory. Advanced Engineering Informatics, 53, 101679. DOI: https://doi.org/10.1016/j.aei.2022.101679
  • Zheng, L., Zhan, X., Zhang, X. (2020). Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera. Sensors, 20, 6752. DOI: https://doi.org/10.3390/s20236752
  • Zuo, Z. (2010). Trajectory tracking control design with command-filtered compensation for a quad-rotor, IET Control Theory Appl., 4, (11), 2343–2355. DOI: https://doi.org/10.1049/iet-cta.2009.0336
There are 23 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other)
Journal Section Makaleler
Authors

Muharrem Mercimek 0000-0001-8737-298X

Onur Sarıpınar This is me 0000-0001-6042-5930

Early Pub Date December 12, 2023
Publication Date December 22, 2023
Submission Date June 23, 2023
Published in Issue Year 2023 Volume: 9 Issue: 4

Cite

APA Mercimek, M., & Sarıpınar, O. (2023). Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor. Journal of Advanced Research in Natural and Applied Sciences, 9(4), 1005-1019. https://doi.org/10.28979/jarnas.1318975
AMA Mercimek M, Sarıpınar O. Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor. JARNAS. December 2023;9(4):1005-1019. doi:10.28979/jarnas.1318975
Chicago Mercimek, Muharrem, and Onur Sarıpınar. “Position Control Using Trajectory Tracking and State Estimation of a Quad-Rotor”. Journal of Advanced Research in Natural and Applied Sciences 9, no. 4 (December 2023): 1005-19. https://doi.org/10.28979/jarnas.1318975.
EndNote Mercimek M, Sarıpınar O (December 1, 2023) Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor. Journal of Advanced Research in Natural and Applied Sciences 9 4 1005–1019.
IEEE M. Mercimek and O. Sarıpınar, “Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor”, JARNAS, vol. 9, no. 4, pp. 1005–1019, 2023, doi: 10.28979/jarnas.1318975.
ISNAD Mercimek, Muharrem - Sarıpınar, Onur. “Position Control Using Trajectory Tracking and State Estimation of a Quad-Rotor”. Journal of Advanced Research in Natural and Applied Sciences 9/4 (December 2023), 1005-1019. https://doi.org/10.28979/jarnas.1318975.
JAMA Mercimek M, Sarıpınar O. Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor. JARNAS. 2023;9:1005–1019.
MLA Mercimek, Muharrem and Onur Sarıpınar. “Position Control Using Trajectory Tracking and State Estimation of a Quad-Rotor”. Journal of Advanced Research in Natural and Applied Sciences, vol. 9, no. 4, 2023, pp. 1005-19, doi:10.28979/jarnas.1318975.
Vancouver Mercimek M, Sarıpınar O. Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor. JARNAS. 2023;9(4):1005-19.


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