An Introduction to Parallel Control and Management for High-Speed Railway Systems

Ning, Bin; Tang, Tao; Dong, Hairong; Wen, Ding; Liu, Derong; Gao, Shigen; Wang, Jing

doi:10.1109/tits.2011.2159789

Cited by 110 publications

(33 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most advanced cities are dependent on reliable and safe rail networks to carry a large number of commuters from their homes to offices and then back homes [3,9,11,12]. Moreover, tourists today are also relying on rail networks to travel from one scenic spot to another scenic spot in many cities.…”

Section: In 1953mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…[3,9] According to the official Xinhua News Agency [10], China invested 745.5 billion yuan (USD115 billion) in building railways in 2011 alone. As at the end of 2010, China had already taken the lead with more than 7000 km of high-speed railways in service in the world [9]. As the inter-city high-speed railway system that is a complex system involving engineering, social, and economic factors is affected by climatic and human factors, Ning et al [9] developed parallel control and management system that incorporates artificial systems, computational experiments, and parallel execution (ACP) for rail planning and management.…”

Section: Introductionmentioning

confidence: 99%

“…As at the end of 2010, China had already taken the lead with more than 7000 km of high-speed railways in service in the world [9]. As the inter-city high-speed railway system that is a complex system involving engineering, social, and economic factors is affected by climatic and human factors, Ning et al [9] developed parallel control and management system that incorporates artificial systems, computational experiments, and parallel execution (ACP) for rail planning and management. This ACP method and other complex network theories have also been applied to study system behaviors of urban rail transportation systems [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…To address such concerns, this paper describes an alternative approach that has five centrality measures (following the suggestions from Ning et al [9,11,12] who advocate the interaction between humans and engineering systems). Centrality measures have been developed in the social network analysis community since the 1950s.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Centrality of an Urban Rail System

2015

Urban Rail Transit

View full text Add to dashboard Cite

Railway re-emerges as one of the most important man-made physical systems in the world. Hundreds of million passengers travel by trains within cities. Hence, the management and maintenance of rail and station facilities are crucial. The paper introduces five centrality measures and explains whether and how these measures can be applied to the network analysis of urban rail systems. Centrality measures were used to identify the characteristics of Hong Kong's urban rail system. Results showed that betweenness centrality is the most appropriate measure to indicate the relative importance of a station based on its potential on strategic facility management and risk management in an urban rail system.

show abstract

Section: In 1953mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Centrality of an Urban Rail System

2015

Urban Rail Transit

View full text Add to dashboard Cite

show abstract

Composite Disturbance‐Observer‐Based Control and Control for High Speed Trains with Actuator Faults

Dong

Lin

Yao

et al. 2017

Asian Journal of Control

Self Cite

View full text Add to dashboard Cite

To guarantee the position and velocity tracking performance of high speed trains (HSTs) with actuator faults, a composite control algorithm consisting of the disturbance‐observer‐based control (DOBC) and ℋ∞ control is proposed. Based on the multiple point‐mass model, the dynamics of HSTs is established by a cascade of carriages which are connected by flexible couplers, during the procedure of which, the running resistance, actuator faults and multiple disturbances are taken into account. The multiple disturbances are composed of two parts, one of which is the ramp resistance due to the track slope, the other is unknown gusts which can be modeled as a harmonic disturbance with time‐varying frequency. The unknown gusts is estimated and rejected via the DOBC methodology, meanwhile, the running resistance and the ramp resistance are attenuated by the ℋ∞ control methodology. According to the Lyapunov stability analysis and LMI‐based algorithms, main results are derived such that the closed‐loop system is asymptotically stable and the desired performance can be guaranteed. Compared with the numeral simulation results with the single ℋ∞ control method, it is demonstrated that the proposed control methodology is more effective and the system has a higher precision of position and velocity tracking.

show abstract

Effect of Crosswind Angle on the Surface Pressure Distribution of Intercity Trains on Viaducts Under Wind-Driven Rain Environment

Zeng,

Chen,

et al. 2023

Mechanisms and Machine Science

View full text Add to dashboard Cite

An Introduction to Parallel Control and Management for High-Speed Railway Systems

Cited by 110 publications

References 29 publications

Centrality of an Urban Rail System

Centrality of an Urban Rail System

Composite Disturbance‐Observer‐Based Control and Control for High Speed Trains with Actuator Faults

Effect of Crosswind Angle on the Surface Pressure Distribution of Intercity Trains on Viaducts Under Wind-Driven Rain Environment

Contact Info

Product

Resources

About