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Mathematical Problems in Engineering
Volume 2015, Article ID 946952, 6 pages
http://dx.doi.org/10.1155/2015/946952
Research Article

New Viewpoints about Pseudo Measurements Method in Equality-Constrained State Estimation

College of Mathematics, Sichuan University, Chengdu, Sichuan 610064, China

Received 4 October 2014; Revised 20 February 2015; Accepted 25 February 2015

Academic Editor: Elmetwally Elabbasy

Copyright © 2015 Bingjie Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. Massicotte, R. Z. Morawski, and A. Barwicz, “Incorporation of a positivity constraint into a Kalman-filter-based algorithm for correction of spectrometric data,” IEEE Transactions on Instrumentation and Measurement, vol. 44, no. 1, pp. 2–7, 1995. View at Publisher · View at Google Scholar · View at Scopus
  2. A. T. Alouani and W. D. Blair, “Use of a kinematic constraint in tracking constant speed, maneuvering targets,” IEEE Transactions on Automatic Control, vol. 38, no. 7, pp. 1107–1111, 1993. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. T. Kirubarajan, Y. Bar-Shalom, and K. R. Pattipati, “Ground target tracking with variable structure IMM estimator,” IEEE Transactions on Aerospace and Electronic Systems, vol. 36, no. 1, pp. 26–46, 2000. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Spong, S. Hutchinson, and M. Vidyasagar, Robot Modeling and Control, John Wiley & Sons, 2005.
  5. W. Wen and H. F. Durrant-Whyte, “Model based active object localisation using multiple sensors,” in Proceedings of the IEEE/RSJ International Workshop on Intelligent Robots and Systems (IROS '91), vol. 3, pp. 1448–1452, Osaka, Japan, November 1991. View at Publisher · View at Google Scholar
  6. W. Wen and H. F. Durrant-Whyte, “Model-based multi-sensor data fusion,” in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1720–1726, May 1992. View at Scopus
  7. J. Porrill, “Optimal combination and constraints for geometrical sensor data,” International Journal of Robotics Research, vol. 7, no. 6, pp. 66–77, 1988. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Pizzinga, “Constrained Kalman filtering: additional results,” International Statistical Review, vol. 78, no. 2, pp. 189–208, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. T. L. Chia, P.-C. Chow, and H. J. Chizeck, “Recursive parameter identification of constrained systems: an application to electrically stimulated muscle,” IEEE Transactions on Biomedical Engineering, vol. 38, no. 5, pp. 429–442, 1991. View at Publisher · View at Google Scholar · View at Scopus
  10. R. Zanetti, M. Majji, R. H. Bishop, and D. Mortari, “Norm-constrained kalman filtering,” Journal of Guidance, Control, and Dynamics, vol. 32, no. 5, pp. 1458–1465, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. R. J. Hewett, M. T. Heath, M. D. Butala, and F. Kamalabadi, “A robust null space method for linear equality constrained state estimation,” IEEE Transactions on Signal Processing, vol. 58, no. 8, pp. 3961–3971, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  12. H. Wu, W. Wang, and H. Ye, “Model reduction based set-membership filtering with linear state equality constraints,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 2, pp. 1391–1399, 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. T. L. Song, J. Y. Ahn, and C. Park, “Suboptimal filter design with pseudomeasurements for target tracking,” IEEE Transactions on Aerospace and Electronic Systems, vol. 24, no. 1, pp. 28–39, 1988. View at Publisher · View at Google Scholar · View at Scopus
  14. M. Tahk and J. L. Speyer, “Target tracking problems subject to kinematic constraints,” in Proceedings of the IEEE Conference on Decision and Control, pp. 1058–1059, 1988.
  15. M. Tahk and J. L. Speyer, “Target tracking problems subject to kinematic constraints,” IEEE Transactions on Automatic Control, vol. 35, no. 3, pp. 324–326, 1990. View at Publisher · View at Google Scholar · View at Scopus
  16. H. E. Doran, “Constraining Kalman filter and smoothing estimates to satisfy time-varying restrictions,” The Review of Economics and Statistics, vol. 74, no. 3, pp. 568–572, 1992. View at Publisher · View at Google Scholar
  17. D. Simon, “Kalman filtering with state constraints: a survey of linear and nonlinear algorithms,” IET Control Theory and Applications, vol. 4, no. 8, pp. 1303–1318, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  18. Z. S. Duan and X. R. Li, “The role of pseudo measurements in equality-constrained state estimation,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 3, pp. 1654–1666, 2013. View at Publisher · View at Google Scholar · View at Scopus
  19. K. Mahata and T. Söderström, “Improved estimation performance using known linear constraints,” Automatica, vol. 40, no. 8, pp. 1307–1318, 2004. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. D. Simon and T. L. I. Chia, “Kalman filtering with state equality constraints,” IEEE Transactions on Aerospace and Electronic Systems, vol. 38, no. 1, pp. 128–136, 2002. View at Publisher · View at Google Scholar · View at Scopus
  21. S. Ko and R. R. Bitmead, “State estimation for linear systems with state equality constraints,” Automatica, vol. 43, no. 8, pp. 1363–1368, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  22. N. Gupta and R. Hauser, “Kalman filtering with equality and inequality state constraints,” Oxford University Numerical Analysis Group Technical Report, University of Oxford, Oxford, UK, 2007. View at Google Scholar
  23. D. Simon and D. L. Simon, “Constrained Kalman filtering via density function truncation for turbofan engine health estimation,” International Journal of Systems Science, vol. 41, no. 2, pp. 159–171, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. N. Gupta, “Kalman Filtering in the presence of state space equality constraints,” in Proceedings of the IEEE 26th Chinese Control Conference (CCC '07), pp. 107–113, Hunan, China, July 2007. View at Publisher · View at Google Scholar
  25. N. Gupta and R. Hauser, “Mathematically equivalent approaches for equality constrained kalman filtering,” Oxford University Numerical Analysis Group Technical Report, Oxford University, Oxford, UK, 2009. View at Google Scholar
  26. B. O. S. Teixeira, J. Chandrasekar, L. A. B. Tôrres, L. A. Aguirre, and D. S. Bernstein, “State estimation for linear and non-linear equality-constrained systems,” International Journal of Control, vol. 82, no. 5, pp. 918–936, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  27. B. D. O. Anderson and J. B. Moore, Optimal Filtering, Prentice-Hall, Englewood Cliffs, NJ, USA, 1979.