State Estimation for Linear Discrete Systems with Unknown Input Using Compensations
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The problem of construction of state estimations for linear systems with discrete time is considered in the presence of unknown input in the model of the object. A modification of the Kalman filter algorithm using compensation for the constant component and estimation of the unknown changing input component by the least squares method is suggested. Results of statistical simulation are presented. The algorithm can be used for solving problems of processing of information obtained as a result of observations over physical processes.
Keywordsstate estimation linear system unknown input Kalman filtering
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