DOI QR코드

DOI QR Code

Inertia tensor estimation for a rigid nadir pointing satellite based on star tracker

  • Cheriet, Mohammed E.A. (Department of Space Mechanics Research, Satellite Development Center) ;
  • Bellar, Abdellatif (Department of Space Mechanics Research, Satellite Development Center) ;
  • Ghaffour, Mohammed Y. (Department of Space Mechanics Research, Satellite Development Center) ;
  • Adnane, Akram (Department of Space Mechanics Research, Satellite Development Center) ;
  • Mohammed, Mohammed A. SI (Department of Space Mechanics Research, Satellite Development Center)
  • Received : 2020.09.02
  • Accepted : 2021.03.04
  • Published : 2021.03.25

Abstract

Accurate inertia properties information is important to reach an optimized estimation of attitude and precise control of a rigid spacecraft. Unfortunately, the satellite is succumbing several influences that can affect the inertia properties, such as fuel consumption and sloshing. Thus, this work inspects the use of star tracker to estimate the attitude, angular velocity and moment of inertia for a rigid nadir pointing satellite by employing extended Kalman filter, without any prior information about the nominal inertia matrix. The proposed estimator is applied in nadir pointing mode and without any constant control torque to avoid the attitude tumbling during the estimation phase, which in turn leads to a catastrophic failure of the satellite mission. The simulation results are compared to three other approaches and validated by Monte Carlo method that elucidates the good performance of the suggested approach and demonstrates its efficiency in satellite inertia tensor and attitude estimation even in worst situations.

Keywords

References

  1. Adnane, A., Foitih, Z.A., Mohammed, M.A.S. and Bellar, A. (2018), "Real-time sensor fault detection and isolation for LEO satellite attitude estimation through magnetometer data", Adv. Sp. Res., 61(4), 1143-1157. https://doi.org/10.1016/j.asr.2017.12.007.
  2. Bellar, A. and Mohammed, M.A.S. (2019), "Satellite inertia parameters estimation based on extended Kalman Filter", J. Aerosp. Technol. Manage., 11, 1-11. https://doi.org/10.5028/jatm.v11.1016.
  3. Bergmann, E. and Dzielski, J. (1990), "Spacecraft mass property identification with torque-generating control", J. Guid. Control Dynam., 13(1), 99-103. https://doi.org/10.2514/3.20522.
  4. Bergmann, E.V., Walker, B.K. and Levy, D.R. (1987), "Mass property estimation for control of asymmetrical satellites", J. Guid. Control Dynam., 10(5), 483-491. https://doi.org/10.2514/3.20243.
  5. Bordany, R., Steyn, W.H. and Crawford, M. (2000), "In-orbit estimation of the inertia matrix and thruster parameters of UoSAT-12", Proceedings of the 14th AIAA/USU Conference on Small Satellites, Logan, U.S.A., August.
  6. Chashmi, S.Y.N. and Malaek, S.M.B. (2016), "Fast estimation of space-robots inertia parameters: A modular mathematical formulation", Acta Astronautica, 127, 283-295. https://doi.org/10.1016/j.actaastro.2016.04.037.
  7. Keim, J.A., Acikmese, A.B. and Shields, J.F. (2006), "Spacecraft inertia estimation via constrained least squares", Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, U.S.A., March.
  8. Kim, D., Yang, S. and Lee, S. (2016), "Rigid body inertia estimation using extended Kalman and SavitzkyGolay filters", Math. Probl. Eng., 1-7. https://doi.org/10.1155/2016/2962671.
  9. Kim, D.H., Yang, S., Cheon, D.I., Lee, S. and Oh, H.S. (2010), "Combined estimation method for inertia properties of STSAT-3", J. Mech. Sci. Technol., 24(8), 1737-1741. https://doi.org/10.1007/s12206-010-0521-2.
  10. Kutlu, A., Haciyev, C. and Tekinalp, O. (2007), "Attitude determination and rotational motion parameters identification of a LEO satellite through magnetometer and sun sensor data", Proceedings of the 3rd International Conference on Recent Advances in Space Technologies, Istanbul, Turkey, June.
  11. Linares, R., Leve, F.A., Jan, M.K. and Crassidis, J.L. (2012), "Space object mass-specific inertia matrix estimation from photometric data", Adv. Astronaut. Sci., 144, 41-54.
  12. Lorenzetti, J S., Banuelos, L., Clarke, R., Murillo, O.J. and Bowers, A. (2017), "Determining products of inertia for small scale UAVs", Proceedings of the 55th AIAA Aerospace Sciences Meeting, Grapevine, Texas, U.S.A., January.
  13. Manchester, Z. R. and Peck, M. A. (2017), "Recursive inertia estimation with semidefinite programming", Proceedings of the AIAA Guidance, Navigation, and Control Conference, Grapevine, Texas, U.S.A., January.
  14. Muliadi, J., Langit, R. and Kusumoputro, B. (2017), "Estimating the UAV moments of inertia directly from its flight data", Proceedings of the 15th International Conference on Quality in Research (QiR): International Symposium on Electrical and Computer Engineering, Nusa Dua, Indonesia, July.
  15. Ni, Z., Wu, Z., Liu, J. and Shen, X. (2017), "On-orbit identification of time-varying moment of inertia for spacecraft based on a recursive subspace method", Proceedings of the 36th Chinese Control Conference (CCC), Dalian, China, July.
  16. Palimaka, J. and Burlton, B. (1992), "Estimation of spacecraft mass properties using angular rate gyro data", Proceedings of the Guidance, Navigation and Control Conference, Hilton Head Island, South Carolina, U.S.A., August.
  17. Salem, F.A. and Aly, A.A. (2015), "PD controller structures: Comparison and selection for an electromechanical system", Int. J. Intell. Syst. Appl., 7(2), 1-12. https://doi.org/10.5815/ijisa.2015.02.01.
  18. Sidi, M.J. (1997), Spacecraft Dynamics and Control: A Practical Engineering Approach, Cambridge University Press, Cambridge, U.K.
  19. Tanygin, S. and Williams, T. (1997), "Mass property estimation using coasting maneuvers", J. Guid. Control Dynam., 20(4), 625-632. https://doi.org/10.2514/2.4099.
  20. Thienel, J., Luquette, R. and Sanner, R. (2008), "Estimation of spacecraft inertia parameters", Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Honolulu, Hawaii, U.S.A., August.
  21. Wertz, J. R. (2012), Spacecraft Attitude Determination and Control, Springer Science and Business Media, Berlin, Germany.
  22. Wie, B., Weiss, H. and Arapostathis, A. (1989), "Quarternion feedback regulator for spacecraft eigenaxis rotations", J. Guid. Control Dynam., 12(3), 375-380. https://doi.org/10.2514/3.20418.
  23. Xu, B. and Wang, S. (2017), "Vision-based moment of inertia estimation of non-cooperative space object", Proceedings of the 10th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, China, December.
  24. Yadegari, H., Khouane, B., Yukai, Z. and Chao, H. (2018), "Disturbance observer based anti-disturbance fault tolerant control for flexible satellites", Adv. Aircraft Spacecraft Sci., 5(4), 459-475. https://doi.org/10.12989/aas.2018.5.4.459.
  25. Yang, S., Lee, S., Lee, J.H. and Oh, H.S. (2015), "New real-time estimation method for inertia properties of STSAT-3 using gyro data", T. Japan Soc. Aeronaut. Sp. Sci., 58(4), 247-249. https://doi.org/10.2322/tjsass.58.247.
  26. Yang, Y. and Zhou, Z. (2017), "Attitude estimation: with or without spacecraft dynamics?", Adv. Aircraft Spacecraft Sci., 4(3), 335-351. https://doi.org/10.12989/aas.2017.4.3.335.
  27. Yoon, H., Riesing, K.M. and Cahoy, K. (2017), "Kalman filtering for attitude and parameter estimation of nanosatellites without gyroscopes", J. Guid. Control Dynam., 40(9), 2272-2288. https://doi.org/10.2514/1.G002649.
  28. Zhai, K., Wang, T. and Meng, D. (2017), "Optimal excitation design for identifying inertia parameters of spacecraft". Acta Astronautica, 140, 370-379. https://doi.org/10.1016/j.actaastro.2017.08.002.
  29. Zhao, Y., Zhang, D., Tian, H. and Li, N. (2009), "Mass property estimation for mated flight control", Proceedings of the International Conference on Computer Modeling and Simulation, Macau, China, February.