Optimal filtering in discrete-time systems with time delays and Markovian jump parameters

Chunyan Han, Huanshui Zhang

Abstract


This paper investigates the linear minimum mean square error estimation for discrete-time Markovian jump linear systems with delayed measurements. The key technique applied for treating the measurement delay is reorganization innovation analysis, by which the state estimation with delayed measurements is transformed into a standard linear mean-square filter of an associated delay-free system. The optimal filter is derived based on the innovation analysis method together with geometric arguments in an appropriate Hilbert space. The solution is given in terms of two Riccati difference equations. Finally, a simulation example is presented to illustrate the efficiency of the proposed method.


doi:10.1017/S1446181110000076

Keywords


Markovian jump linear systems, time-delay systems, optimal filterning, reorganized innovation analysis, Riccati equations



DOI: http://dx.doi.org/10.21914/anziamj.v51i0.1750



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ANZIAM Journal, ISSN 1446-8735, copyright Australian Mathematical Society.