http://iet.metastore.ingenta.com
1887

Kalman filtering for continuous-time systems with multiple delayed measurements

Kalman filtering for continuous-time systems with multiple delayed measurements

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The paper focuses on the Kalman filtering problem for linear continuous-time systems with multiple delayed measurements. An explicit and simpler solution to the Kalman filtering problem is presented for such systems. The approach applied is the reorganised innovation analysis. The obtained Kalman filter is given in terms of Riccati differential equations. A numerical example is given to demonstrate the proposed approach.

References

    1. 1)
      • N. Wiener . (1949) Extrapolation interpolation, and smoothing of stationary time series.
    2. 2)
      • B.D.O. Anderson , J.R. Moore . (1979) Optimal filtering.
    3. 3)
      • B. Hassibi , A.H. Sayed , T. Kailath . (1999) Indefinite quadratic estimation and control: a unified approach to .
    4. 4)
      • T. Kailath , A.H. Sayed , B. Hassibi . (1999) Linear Estimation.
    5. 5)
      • J.M. Mendel . (1995) Lessons in estimation thoery for signal processing, communications, and control.
    6. 6)
    7. 7)
      • Briggs, M.S.: `Filtering of linear heredity systems with delays in the input', 1980, PhD, Imperial College, UK.
    8. 8)
      • N. Briggs , R. Vinter . Linear filtering for time-delay systems. IMA J. Math. Control Inf. , 167 - 178
    9. 9)
      • H. Kwakernaak . Optimal filtering in linear systems with time delays. IEEE Trans. Autom. Control. , 169 - 173
    10. 10)
      • H. Kwong , A.S. Willsky . Estimation and filter stability of stochastic delay systems. SIAM J. Control Optim. , 660 - 681
    11. 11)
    12. 12)
      • Lu, X., Zhang, H., Wang, W.: `A reorganized innovation approach to kalman filtering for time-varying system', Proc. Int. Conf. on Impulsive Dynamic Systems and Applications, 2006, Qingdao, China, p. 1169–1173.
    13. 13)
    14. 14)
    15. 15)
      • K. Uchida , K. Ikeda , T. Azuma . Finite-dimensional characterizations of H∞ control for linear systems with delays in input and output. Int. J. Robust Nonlin. Control , 9 , 833 - 843
    16. 16)
      • W. Zhang , S.B. Chen , C.S. Tseng . Robust H∞ filtering for nonlinear stochastic systems. IEEE Trans. Signal Process. , 2 , 289 - 298
    17. 17)
      • R.E. Kalman . A new approach to linear filtering and prediction problems. Trans. ASME-D, J. Basic Eng. , 1 , 35 - 45
    18. 18)
    19. 19)
      • H. Zhang , L. Xie , Y.C. Soh . H∞ fixed-lag smoothing for linear time-varying discrete time systems. Automatica , 5 , 839 - 846
    20. 20)
      • X. Lu , H. Zhang , W. Wang , K.L. Teo . Kalman filtering for multiple time delay measurements. Automatica , 8 , 1455 - 1461
    21. 21)
    22. 22)
      • L.A. Klein . (1999) Sensor and data fusion concepts and applications.
    23. 23)
    24. 24)
      • G.R. Duan , H.Q. Wang . Multi-model switching control and its application to BTT missile design. Acta Aeronaut. Astronaut. Sin. , 2 , 144 - 147
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-spr_20060045
Loading

Related content

content/journals/10.1049/iet-spr_20060045
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address