Speed tracking control for high-speed train with an Elman model
YANG Hui
LIU Pan
LI Zhong-qi
Abstract：High-speed trains have high running speed, complex operation process and strong nonlinearity, which make difficulty for their high-precision modeling and control. To guarantee the safety of the high-speed trains' running process, this paper presents a modeling method and a speed tracking control scheme for their running process. A method of data-driven modeling is employed to establish the Elman model for the running process of the high-speed train, and a modified generalized predictive control algorithm is used to develop a speed tracking controller to realize the speed tracking. The simulation results based on the CRH380AL operation process data indicate that the method presented in the paper can realize the safe and accurate running of high-speed trains, and the method makes higher precision and higher robustness.
Keywords：high-speed trainsystem identificationgeneralized predictive controlElman neural networkdata-driven
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 125-130 )