A Barrier Lyapunov Function (BLF) based Approach for Antiskid Traction/Braking Control of High Speed Trains

被引：0

作者：

Yang, Wanqing ^{[1
]}

Cai, Wenchuan ^{[1
]}

Song, Yongduan ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Beijing 100044, Peoples R China

来源：

26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC) | 2014年

关键词：

Antiskid Control; Traction /Braking Control; Barrier Lyapunov Function (BLF);

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Antiskid is an important factor that directly impacts safe operation of high-speed trains (HST). However, if the antiskid control is designed independently from the traction/braking unit, as usually the case in most existing methods, the traction/braking control performance might be degraded. In this work, the antiskid constraint is directly linked with the development of traction/braking control system, which of course renders the underlying problem rather complicated. A barrier Lyapunov function (BLF) based approach is utilized to solve this problem, resulting in a control scheme capable of ensuring stable traction/braking operation and at the same time preventing possible wheel skid and improving the performance of the traction/braking system. Both theoretical analysis and numerical simulation validate the effectiveness of the proposed control.

引用

页码：5023 / 5028

页数：6

共 50 条

[31] Neuro-adaptive fault-tolerant control of high speed trains under traction-braking failures using self-structuring neural networks
Gao, Rui-Zhen
Wang, Yu-Juan
Lai, Jun-Feng
Gao, Hui
INFORMATION SCIENCES, 2016, 367 : 449 - 462
[32] Fault diagnosis on the bearing of traction motor in high-speed trains based on deep learning
Zou, Yingyong
Zhang, Yongde
Mao, Hancheng
ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (01) : 1209 - 1219
[33] Estimating traction energy consumption of high-speed trains based on BP neural network
Wang D.
Ma W.
Li L.
Yang Y.
Xiang C.
Li, Liqing (liqingli@hotmail.com), 2017, Central South University of Technology (48): : 1104 - 1110
[34] A Control Barrier Function Perspective on Lyapunov-Based Economic Model Predictive Control
Durand, Helen
Ames, Aaron D.
2022 AMERICAN CONTROL CONFERENCE, ACC, 2022, : 2823 - 2828
[35] Braking curves for high speed traffic with radio based train control
ZEV-Zeitschrift fuer Eisenbahnwesen und Verkehrstechnik - Journal for Railway and Transport, 1999, 123 (02): : 53 - 60
[36] Sliding Mode Adaptive Robust Control for High-Speed Trains Based on Improved Approach Rate
Zhang, Tong
Wang, Zhiyu
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 1750 - 1755
[37] Online Accurate Estimation of the Wheel-Rail Adhesion Coefficient and Optimal Adhesion Antiskid Control of Heavy-Haul Electric Locomotives Based on Asymmetric Barrier Lyapunov Function
Zhao, Kaihui
Li, Peng
Zhang, Changfan
He, Jing
Li, Yanfei
Yin, Tonghuan
JOURNAL OF SENSORS, 2018, 2018
[38] Adaptive Tracking Control of State Constraint Systems Based on Differential Neural Networks: A Barrier Lyapunov Function Approach
Fuentes-Aguilar, Rita Q.
Chairez, Isaac
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (12) : 5390 - 5401
[39] Exponential Control Lyapunov-Barrier Function Using a Filtering-Based Concurrent Learning Adaptive Approach
Azimi, Vahid
Hutchinson, Seth
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2022, 67 (10) : 5376 - 5383
[40] Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
Sadeghzadeh-Nokhodberiz, Nargess
Meskin, Nader
IEEE ACCESS, 2023, 11 : 142916 - 142930

← 1 2 3 4 5 →