151-0566-00L  Recursive Estimation

SemesterFrühjahrssemester 2020
DozierendeR. D'Andrea
Periodizitätjährlich wiederkehrende Veranstaltung

KurzbeschreibungEstimation of the state of a dynamic system based on a model and observations in a computationally efficient way.
LernzielLearn the basic recursive estimation methods and their underlying principles.
InhaltIntroduction to state estimation; probability review; Bayes' theorem; Bayesian tracking; extracting estimates from probability distributions; Kalman filter; extended Kalman filter; particle filter; observer-based control and the separation principle.
SkriptLecture notes available on course website: Link
Voraussetzungen / BesonderesRequirements: Introductory probability theory and matrix-vector algebra.