Title :
On bad data suppression in estimation
Author_Institution :
Brown Boveri Research Center, Baden, Switzerland
fDate :
12/1/1972 12:00:00 AM
Abstract :
Merrill and Schweppe [1] propose a modification of the usual least squares criterion for estimation in order to suppress bad data. It is shown that similar estimators can be obtained from maximum likelihood theory.
Keywords :
State estimation; maximum-likelihood (ML) estimation; Control systems; Convergence; Cost function; Gradient methods; Least squares approximation; Least squares methods; Maximum likelihood estimation; Stability; Time measurement; Turbines;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1972.1100165
