DocumentCode :
2297096
Title :
Data-based dynamic characteristic modeling and tracking control for high-speed train
Author :
Gao Shi-gen ; Qi Shu-hu ; Dong Hai-rong ; Ning Bin ; Li, Li
Author_Institution :
State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
fYear :
2012
fDate :
6-8 July 2012
Firstpage :
2913
Lastpage :
2917
Abstract :
This paper introduces a novel dynamic characteristic modeling for high-speed train (HST) speed-position tracking control under time-varying, unpredictable and unknown operational environments. This method involves the construction of a dynamic characteristic model and design of a golden-section adaptive controller, which is a data-based model-free controller design approach and requires no precise mathematical description of the plant Based on the above methodology, speed-position tracking control and energy-saving operation problems of HST are studied. The effectiveness and preciseness of the proposed model and corresponding controllers are verified via numerical simulations, with high energy efficiency concurrently.
Keywords :
adaptive control; control system synthesis; energy conservation; position control; railways; time-varying systems; tracking; velocity control; HST speed-position tracking control; data-based dynamic characteristic modeling; data-based model-free controller design approach; energy efficiency; energy-saving operation problems; golden-section adaptive controller design; high-speed train; mathematical description; numerical simulations; time-varying operational environment; unknown operational environments; unpredictable operational environment; Adaptation models; Numerical models; Tracking control; dynamic characteristic modeling; golden-section adaptive controller; high-speed train;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
Type :
conf
DOI :
10.1109/WCICA.2012.6358368
Filename :
6358368
Link To Document :
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