DocumentCode
592373
Title
A norm optimal iterative learning control based train trajectory tracking approach
Author
Heqing Sun ; Zhongsheng Hou ; Dayou Li
Author_Institution
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
fYear
2012
fDate
10-13 Dec. 2012
Firstpage
3966
Lastpage
3971
Abstract
A norm optimal iterative learning control (NOILC) is proposed and applied in train trajectory tracking problem, and it then is extended to the cases with traction/braking constraint. Rigorous theoretical analysis has shown that the proposed approach can guarantee the asymptotic convergence of train speed and position to desired profiles as iteration number goes infinity. Simulation results further demonstrate the effectiveness of the proposed NOILC approach.
Keywords
adaptive control; iterative methods; learning systems; optimal control; railways; trajectory control; NOILC; asymptotic convergence; braking constraint; norm optimal iterative learning control; railways; traction constraint; train trajectory tracking approach; Convergence; Dynamics; Equations; Force; Load modeling; Mathematical model; Trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location
Maui, HI
ISSN
0743-1546
Print_ISBN
978-1-4673-2065-8
Electronic_ISBN
0743-1546
Type
conf
DOI
10.1109/CDC.2012.6426487
Filename
6426487
Link To Document