DocumentCode :
3139316
Title :
An iterative predictive learning control approach with application to train trajectory tracking
Author :
Heqing Sun ; Zhongsheng Hou
Author_Institution :
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
fYear :
2013
fDate :
23-26 June 2013
Firstpage :
1
Lastpage :
6
Abstract :
An approach of iterative predictive learning control (IPLC) is proposed for the control of train trajectory tracking. Through combining iterative learning control with predictive control method, the iterative predictive learning control for input-affine nonlinear systems is formulated and solved in this paper. Its application to train trajectory tracking is detailed. Rigorous theoretical analysis confirms that the proposed approach can guarantee the asymptotic convergence of train speed and position to desired profiles along iteration axis. Simulation result shows its effectiveness and feasibility.
Keywords :
iterative methods; learning systems; nonlinear control systems; position control; predictive control; railways; trajectory control; velocity control; IPLC; asymptotic convergence; input-affine nonlinear systems; iteration axis; iterative predictive learning control approach; train position; train speed; train trajectory tracking; Dynamics; Equations; Iterative methods; Mathematical model; Resistance; Trajectory; Vehicle dynamics; Iterative learning control; Predictive control; Train trajectory tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (ASCC), 2013 9th Asian
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-5767-8
Type :
conf
DOI :
10.1109/ASCC.2013.6606355
Filename :
6606355
Link To Document :
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