Optimal Filtering for Linear Discrete-Time Systems with Single Delayed Measurement

This paper aims to present a polynomial approach to the steady-state optimal filtering for delayed systems. The design of the steady-state filter involves solving one polynomial equation and one spectral factorization. The key problem in this paper is the derivation of spectral factorization for systems with delayed measurement, which is more difficult than the standard systems without delays. To get the spectral factorization, we apply the reorganized innovation approach. The calculation of spectral factorization comes down to two Riccati equations with the same dimension as the original systems.

[1]  Ali H. Sayed,et al.  A survey of spectral factorization methods , 2001, Numer. Linear Algebra Appl..

[2]  Richard Vinter,et al.  Linear Filtering for Time-Delay Systems , 1989 .

[3]  Vladimír Kuera,et al.  Brief papers: New results in state estimation and regulation , 1981 .

[4]  HaeJeong Yang,et al.  Sub-micron Control Algorithm for Grinding and Polishing Aspherical Surface , 2008 .

[5]  H. Kwakernaak,et al.  Optimal filtering in linear systems with time delays , 1967, IEEE Transactions on Automatic Control.

[6]  Michel Gevers,et al.  An innovations approach to the discrete-time stochastic realization problem , 1978 .

[7]  David Zhang,et al.  Hinfinity Fixed-lag smoothing for discrete linear time-varying systems , 2005, Autom..

[8]  U. Shaked A general transfer function approach to linear stationary filtering and steady-state optimal control problems , 1976 .

[9]  Vladimír Kucera,et al.  Efficient algorithm for matrix spectral factorization , 1985, Autom..

[10]  B. Anderson,et al.  Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  Anders Ahlén,et al.  Wiener filter design using polynomial equations , 1991, IEEE Trans. Signal Process..

[12]  J. Jeek,et al.  Paper: Efficient algorithm for matrix spectral factorization , 1985 .

[13]  Lihua Xie,et al.  Optimal and self-tuning deconvolution in time domain , 1999, IEEE Trans. Signal Process..

[14]  Brian D. O. Anderson,et al.  Recursive algorithm for spectral factorization , 1974 .

[15]  Tian-You Chai,et al.  A new method for optimal deconvolution , 1997, IEEE Trans. Signal Process..

[16]  Y.C. Soh,et al.  A reorganized innovation approach to linear estimation , 2004, IEEE Transactions on Automatic Control.

[17]  Vladimír Kucera New results in state estimation and regulation , 1981, Autom..