Optimal pseudo-steady-state estimators for systems with Markovian intermittent measurements

S. Craig Smith, Peter Seiler

Research output: Contribution to journalArticlepeer-review

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Abstract

A state estimator design is described for discrete time systems having observably intermittent measurements. A stationary Markov process is used to model probabilistic measurement losses. The stationarity of the Markov process suggests an analagous stationary estimator design related to the Markov states. A precomputable time-varying state estimator is proposed as an alternative to Kalman's optimal time-varying estimation scheme applied to a discrete linear system with Markovian intermittent measurements. An iterative scheme to find optimal precomputed estimators is given. The results here naturally extend to Markovian jump linear systems.

Original languageEnglish (US)
Pages (from-to)3021-3027
Number of pages7
JournalProceedings of the American Control Conference
Volume4
DOIs
StatePublished - Jan 1 2002

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