Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters

The cruise control of high-speed trains is challenging due to the presence of time-varying air resistance coefficients and control constrains. Because the resistance coefficients for high-speed trains are not accurately known and will change with the actual operating environment, the precision of hi...

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Main Authors: Xiaokang Xu, Jun Peng, Rui Zhang, Bin Chen, Feng Zhou, Yingze Yang, Kai Gao, Zhiwu Huang
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2019/7261726
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author Xiaokang Xu
Jun Peng
Rui Zhang
Bin Chen
Feng Zhou
Yingze Yang
Kai Gao
Zhiwu Huang
author_facet Xiaokang Xu
Jun Peng
Rui Zhang
Bin Chen
Feng Zhou
Yingze Yang
Kai Gao
Zhiwu Huang
author_sort Xiaokang Xu
collection DOAJ
description The cruise control of high-speed trains is challenging due to the presence of time-varying air resistance coefficients and control constrains. Because the resistance coefficients for high-speed trains are not accurately known and will change with the actual operating environment, the precision of high speed train model is lower. In order to ensure the safe and effective operation of the train, the operating conditions of the train must meet the safety constraints. The most traditional cruise control methods are PID control, model predictive control, and so on, in which the high-speed train model is identified offline. However, the traditional methods typically suffer from performance degradations in the presence of time-varying resistance coefficients. In this paper, an adaptive model predictive control (MPC) method is proposed for cruise control of high-speed trains with time-varying resistance coefficients. The adaptive MPC is designed by combining an adaptive updating law for estimated parameters and a multiply constrained MPC for the estimated system. It is proved theoretically that, with the proposed adaptive MPC, the high-speed trains track the desired speed with ultimately bounded tracking errors, while the estimated parameters are bounded and the relative spring displacement between the two neighboring cars is stable at the equilibrium state. Simulations results validate that proposed method is better than the traditional model predictive control.
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issn 0197-6729
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publishDate 2019-01-01
publisher Wiley
record_format Article
series Journal of Advanced Transportation
spelling doaj-art-08a1f7fec2e44df3bd46690b1fb7ddd72025-08-20T02:03:19ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/72617267261726Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying ParametersXiaokang Xu0Jun Peng1Rui Zhang2Bin Chen3Feng Zhou4Yingze Yang5Kai Gao6Zhiwu Huang7School of Information Science and Engineering, Central South University, Changsha 410000, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410000, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410000, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410000, ChinaChangsha University of Science and Technology, Changsha 410000, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410000, ChinaChangsha University of Science and Technology, Changsha 410000, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410000, ChinaThe cruise control of high-speed trains is challenging due to the presence of time-varying air resistance coefficients and control constrains. Because the resistance coefficients for high-speed trains are not accurately known and will change with the actual operating environment, the precision of high speed train model is lower. In order to ensure the safe and effective operation of the train, the operating conditions of the train must meet the safety constraints. The most traditional cruise control methods are PID control, model predictive control, and so on, in which the high-speed train model is identified offline. However, the traditional methods typically suffer from performance degradations in the presence of time-varying resistance coefficients. In this paper, an adaptive model predictive control (MPC) method is proposed for cruise control of high-speed trains with time-varying resistance coefficients. The adaptive MPC is designed by combining an adaptive updating law for estimated parameters and a multiply constrained MPC for the estimated system. It is proved theoretically that, with the proposed adaptive MPC, the high-speed trains track the desired speed with ultimately bounded tracking errors, while the estimated parameters are bounded and the relative spring displacement between the two neighboring cars is stable at the equilibrium state. Simulations results validate that proposed method is better than the traditional model predictive control.http://dx.doi.org/10.1155/2019/7261726
spellingShingle Xiaokang Xu
Jun Peng
Rui Zhang
Bin Chen
Feng Zhou
Yingze Yang
Kai Gao
Zhiwu Huang
Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters
Journal of Advanced Transportation
title Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters
title_full Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters
title_fullStr Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters
title_full_unstemmed Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters
title_short Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters
title_sort adaptive model predictive control for cruise control of high speed trains with time varying parameters
url http://dx.doi.org/10.1155/2019/7261726
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