Improved model-free adaptive control for EMUs velocity tracking system

ZHOU Liang; XIA Jin-feng; LI Zhong-qi

doi:10.19818/j.cnki.1671-1637.2024.02.019

Volume 24 Issue 2

Apr. 2024

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Article Navigation > Journal of Traffic and Transportation Engineering > 2024 > 24(2): 267-280

ZHOU Liang, XIA Jin-feng, LI Zhong-qi. Improved model-free adaptive control for EMUs velocity tracking system[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 267-280. doi: 10.19818/j.cnki.1671-1637.2024.02.019

Citation:

ZHOU Liang, XIA Jin-feng, LI Zhong-qi. Improved model-free adaptive control for EMUs velocity tracking system[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 267-280. doi: 10.19818/j.cnki.1671-1637.2024.02.019

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Improved model-free adaptive control for EMUs velocity tracking system

doi: 10.19818/j.cnki.1671-1637.2024.02.019

ZHOU Liang^{1, 2
,},
XIA Jin-feng³,
LI Zhong-qi^{1, 2
,}

1.
School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, Jiangxi, China
2.
State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure, East China Jiaotong University, Nanchang 330013, Jiangxi, China
3.
CRRC Zhuzhou Electric Locomotive Co., Ltd., Zhuzhou 412001, Hunan, China

Funds:

National Natural Science Foundation of China 52162048

National Natural Science Foundation of China 61991404

Jiangxi Provincial Program for Academic and Technical Leaders Training of Major Disciplines 20213BCJ22002

More Information

Author Bio:
ZHOU Liang(1997-), male, doctoral student, zl971125@163.com

LI Zhong-qi(1975-), male, professor, PhD, lzq0828@163.com
Received Date: 2023-10-03
Available Online: 2024-05-16
Publish Date: 2024-04-30

Abstract

Abstract

To improve the tracking accuracy and stable operation of the train control system, an improved multiple-input multiple-output (MIMO) model-free adaptive control (MFAC) method was proposed. Based on the dynamic linearization technology, the input-output data of each power unit of the system were equivalently transformed into a full form dynamic linearization (FFDL) data model that better fitted the actual operation characteristics of high-speed electric multiple units (EMUs). By incorporating the output error rates into the objective criterion function and weighting the fusion of output errors and output error rates, a new model-free adaptive control scheme with output error rates (MFAC-OER) was derived. The control performance of the algorithm and the equivalent description degree of the system were further improved by delayed estimation of uncertainty factors, such as external disturbances and parameter errors in the FFDL data model. The proposed method was simulated and tested on a CRH380A high-speed EMUs semi-physical test platform equipped in the laboratory to track the actual speed-displacement curve from Jinan to Xuzhou and compare it with some traditional algorithms. Simulation results show that the speed errors of each power unit of EMUs obtained by the MFAC-OER method are within [-0.151, 0.136] km·h^-1, with the control force and acceleration smoothly varying in the ranges of [-48, 42] kN and [-0.785, 0.687] m·s^-2, respectively. The proposed method outperforms the proportional-integral-derivative (PID) and traditional MFAC methods in the control performance. The overall simulation results show that the MFAC-OER method can not only quickly reach the steady state of the system but also possesses good resistance to external disturbances, meeting the tracking accuracy and safety requirements of the EMUs.
- EMUs,
- train automatic driving,
- model-free adaptive control,
- dynamic linearization,
- output error rate,
- disturbance estimation

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References(30)

References

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Improved model-free adaptive control for EMUs velocity tracking system

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