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Active Quantizer-Based Model-Free Adaptive Consensus Tracking for Multiple HSTs Against Sensor Bias

delete2024-01-01
delete3
PRE
AI
W
Wei Yu
D
Deqing Huang *
K
Kai Xu
DOI:10.1109/TIV.2023.3314824delete
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摘要

摘要

En 中文
To enhance traffic efficiency and operational safety of multiple high-speed trains (MHSTs) running on the same track, train-to-train (T2T)-based coordination among train groups has become necessary means. In this article, an active quantizer-based model-free adaptive control (AQMFAC) approach is proposed for MHSTs that accounts for random sensor bias in output channels. Firstly, the design process includes the equivalent linearization of train model, the quantizer establishment, and the controller design. Subsequently, theoretical analysis demonstrates that the proposed AQMFAC can converge speed tracking error to a bounded range. Finally, the AQMFAC scheme is validated using a real-time StarSim hardware-in-the-loop (HIL) semi-physical test platform.
Keyword:
Quantization (signal)
Adaptation models
Actuators
Resistance
Behavioral sciences
Vehicle dynamics
Stability analysis
Active quantizer
model-free adaptive control
consensus tracking
multiple high-speed trains
sensor bias

期刊

I
IEEE Transactions on Intelligent Vehicles
IF:
14.3
论文数:
1.3K
被引数:
1.2W

机构

S
Southwest Jiaotong University
学者数:
2.9W
论文数: 2.1W
被引数: 2.3W
C
Chongqing Jiaotong University
学者数:
6.5K
论文数: 4.3K
被引数: 94
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