Fuzzy-Adaptive Fault-Tolerant Control of High Speed Train Considering Traction/Braking Faults and Nonlinear Resistive Forces

Wang, M. R.; Song, Yongduan; Song, Qi; Han, Peng

doi:10.1007/978-3-642-21090-7_65

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Because of a complicated relationship among fault modes and system mechanisms in trains, the boundaries among failures become blurred [ 168 ]. In recent years, fuzzy theory has been attractive [ 169 , 170 , 171 , 172 ] in diagnosing to high-speed trains.…”

Section: Applications Of Qualitative Ifd Approach In High-speed Trmentioning

confidence: 99%

“…To test the FD performance of fuzzy theory, an adaptive neuro-fuzzy reasoning system is proposed in Reference [ 171 ] to detect several faults in CTCS-3. Research on the adaptive IFD model based on fuzzy theory has attracted attentions, e.g., Reference [ 172 ] takes into account many factors, such as uncertain force and resistance disturbance in high-speed trains, and further proposes fuzzy adaptive reasoning to diagnose actuator faults.…”

Section: Applications Of Qualitative Ifd Approach In High-speed Trmentioning

confidence: 99%

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A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

Cheng

Wang

Chen

et al. 2020

Entropy

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For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch. Therefore, this survey will present a comprehensive review of these qualitative approaches from both theoretical and practical aspects. The primary task of this paper is to review the current development of these qualitative IFD techniques and then to present some of the latest results. Another major focus of our research is to introduce the background of high-speed trains, like the composition of the core subsystems, system structure, etc., based on which it becomes convenient for researchers to extract the diagnostic knowledge of high-speed trains, where the purpose is to understand how to use these types of knowledge. By reasonable utilization of the knowledge, it is hopeful to address various challenges caused by the coupling among subsystems of high-speed trains. Furthermore, future research trends for qualitative IFD approaches are also presented.

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Section: Applications Of Qualitative Ifd Approach In High-speed Trmentioning

confidence: 99%

Section: Applications Of Qualitative Ifd Approach In High-speed Trmentioning

confidence: 99%

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

Cheng

Wang

Chen

et al. 2020

Entropy

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show abstract

“…If the train model is inaccurate, the control performance will be greatly deteriorated. The controllers of the data‐based control methods mainly include neural networks control and fuzzy‐adaptive control [11, 13, 14, 21, 22]. Several data‐driven fault detection schemes have been proposed in [31, 32].…”

Section: Introductionmentioning

confidence: 99%

Model‐free adaptive fault‐tolerant control for subway trains with speed and traction/braking force constraints

Wang

Hou

2020

IET Control Theory & Applications

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Model-Free Adaptive Fault-Tolerant Control for Multiple Point-Mass Subway Trains With Speed and Traction/Braking Force Constraints

2020

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Fuzzy-Adaptive Fault-Tolerant Control of High Speed Train Considering Traction/Braking Faults and Nonlinear Resistive Forces

Cited by 4 publications

References 9 publications

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

Model‐free adaptive fault‐tolerant control for subway trains with speed and traction/braking force constraints

Model-Free Adaptive Fault-Tolerant Control for Multiple Point-Mass Subway Trains With Speed and Traction/Braking Force Constraints

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