Title :
A minimax filter for systems with large plant uncertainties
Author :
Leondes, Cornelius T. ; Pearson, Jack O.
Author_Institution :
University of California, Los Angeles, CA, USA
fDate :
4/1/1972 12:00:00 AM
Abstract :
A minimax filter is derived in order to estimate the state of a system when large uncertainties in the plant dynamics and process noise are present. If the system dynamics and measurements are uncoupled and the noise covariance matrices are diagonal, simple results occur.
Keywords :
Minimax estimation; State estimation; Artificial intelligence; Control system synthesis; Control systems; Covariance matrix; Failure analysis; Filters; Minimax techniques; Regulators; State estimation; Uncertainty;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1972.1099961
