Title :
Unknown parameter identification method using Unscented Kalman Filter for container crane system
Author :
Araki, Nozomu ; Sato, Talmo ; Konishi, Yasuo ; Ishigaki, Hiroyuki
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
Abstract :
This paper describes parameter identification of a container crane system. To control an actual system, it is important to identify its equation of motion including unknown physical parameters. We applied a parameter identification method for a container crane system using the Unscented Kalman Filter (UKF). UKF is a recently developed state estimation method for nonlinear systems, and is applicable even when they have a discontinuity. Our method´s effectiveness has been verified through computer simulation and experiment.
Keywords :
Kalman filters; containers; cranes; nonlinear systems; state estimation; UKF; computer simulation; container crane system; equation of motion; nonlinear systems; parameter identification method; state estimation method; unknown physical parameters; unscented Kalman filter; Containers; Integrated circuit modeling;
Conference_Titel :
Modelling, Identification and Control (ICMIC), The 2010 International Conference on
Conference_Location :
Okayama
Print_ISBN :
978-1-4244-8381-5
Electronic_ISBN :
978-0-9555293-3-7
