Optimal guaranteed cost filtering for Markovian jump discrete-time systems
2004 ◽
Vol 2004
(1)
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pp. 33-48
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Keyword(s):
This paper develops a result on the design of robust steady-state estimator for a class of uncertain discrete-time systems with Markovian jump parameters. This result extends the steady-state Kalman filter to the case of norm-bounded time-varying uncertainties in the state and measurement equations as well as jumping parameters. We derive a linear state estimator such that the estimation-error covariance is guaranteed to lie within a certain bound for all admissible uncertainties. The solution is given in terms of a family of linear matrix inequalities (LMIs). A numerical example is included to illustrate the theory.
2015 ◽
Vol 2015
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pp. 1-12
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Keyword(s):
Keyword(s):
2013 ◽
Vol 2013
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pp. 1-7
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Keyword(s):
2013 ◽
Vol 2013
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pp. 1-10
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Keyword(s):
2008 ◽
Vol 2008
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pp. 1-15
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