Title :
An approximate nonlinear filter for simultaneous estimation of states and parameters in linear stochastic systems
Author_Institution :
Texas Tech University, Lubbock, TX
Abstract :
An approximate nonlinear filter for simultaneous estimation of states and parameters in linear stochastic systems is derived based on some asymptotic considerations. The convergence properties of the approximate nonlinear filter as a parameter estimator for linear stochastic systems are examined and comparisons with other recursive identification algorithms are made.
Keywords :
Atmosphere; Atmospheric modeling; Control systems; Convergence; Kalman filters; Maximum likelihood estimation; Nonlinear control systems; Nonlinear filters; State estimation; Stochastic systems;
Conference_Titel :
Decision and Control, 1985 24th IEEE Conference on
Conference_Location :
Fort Lauderdale, FL, USA
DOI :
10.1109/CDC.1985.268499
