Minimax Identification of Linear Systems by Probability Criterion

The problem of linear estimation of states and parameters of the multidimensional statistically indeterminate system by minimax probability criterion is considered. A priori information about the distribution law of the model random parameters and disturbances is defined by certain constraints on th...

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Bibliographic Details
Main Authors: Pankov, A.R., Popov, A.S., Platonov, E.P., Siemenikhin, K.V.
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
History
Linear systems
Minimax techniques
Multidimensional systems
Optimization methods
Probability distribution
State estimation
Symmetric matrices
Uncertainty
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Description
Summary:The problem of linear estimation of states and parameters of the multidimensional statistically indeterminate system by minimax probability criterion is considered. A priori information about the distribution law of the model random parameters and disturbances is defined by certain constraints on the first-and second-order moments. The explicit form of the minimax probability estimator and the sharp guaranteed bound for the probability functional are provided. The analytic expression of the "worst-case" distribution of the random model parameters is presented.
ISSN:0191-2216
DOI:10.1109/CDC.2005.1583465