Kalman filtering for continuous-time systems with multiple delayed measurements

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Kalman filtering for continuous-time systems with multiple delayed measurements

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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.

Inspec keywords: continuous time filters; Riccati equations; Kalman filters

Other keywords: multiple delayed measurements; Kalman filtering; Riccati differential equations; linear continuous-time systems

Subjects: Linear algebra (numerical analysis); Active filters and other active networks

References

    1. 1)
    2. 2)
      • B. Hassibi , A.H. Sayed , T. Kailath . (1999) Indefinite quadratic estimation and control: a unified approach to .
    3. 3)
      • T. Kailath , A.H. Sayed , B. Hassibi . (1999) Linear Estimation.
    4. 4)
      • H. Kwong , A.S. Willsky . Estimation and filter stability of stochastic delay systems. SIAM J. Control Optim. , 660 - 681
    5. 5)
      • J.M. Mendel . (1995) Lessons in estimation thoery for signal processing, communications, and control.
    6. 6)
    7. 7)
    8. 8)
      • H. Kwakernaak . Optimal filtering in linear systems with time delays. IEEE Trans. Autom. Control. , 169 - 173
    9. 9)
      • X. Lu , H. Zhang , W. Wang , K.L. Teo . Kalman filtering for multiple time delay measurements. Automatica , 8 , 1455 - 1461
    10. 10)
      • G.R. Duan , H.Q. Wang . Multi-model switching control and its application to BTT missile design. Acta Aeronaut. Astronaut. Sin. , 2 , 144 - 147
    11. 11)
      • N. Wiener . (1949) Extrapolation interpolation, and smoothing of stationary time series.
    12. 12)
      • N. Briggs , R. Vinter . Linear filtering for time-delay systems. IMA J. Math. Control Inf. , 167 - 178
    13. 13)
    14. 14)
      • R.E. Kalman . A new approach to linear filtering and prediction problems. Trans. ASME-D, J. Basic Eng. , 1 , 35 - 45
    15. 15)
      • 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.
    16. 16)
      • 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
    17. 17)
    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)
      • W. Zhang , S.B. Chen , C.S. Tseng . Robust H∞ filtering for nonlinear stochastic systems. IEEE Trans. Signal Process. , 2 , 289 - 298
    21. 21)
      • L.A. Klein . (1999) Sensor and data fusion concepts and applications.
    22. 22)
      • B.D.O. Anderson , J.R. Moore . (1979) Optimal filtering.
    23. 23)
    24. 24)
      • Briggs, M.S.: `Filtering of linear heredity systems with delays in the input', 1980, PhD, Imperial College, UK.
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