Hairong Dong

Automatic Train Control System Development and Simulation for High-Speed Railways

Research and development on high-speed railway systems and particularly its automatic control systems, are introduced. Numerical modeling of high-speed trains in the Chinese high-speed train system and its associate automatic control systems are described in detail. Moreover, modeling and simulation of train operation systems are analyzed and demonstrated.

Approximation-Based Robust Adaptive Automatic Train Control: An Approach for Actuator Saturation

This paper addresses an on-line approximation-based robust adaptive control problem for the automatic train operation (ATO) system under actuator saturation caused by constraints from serving motors. A robust adaptive control law is proposed, which is proved capable of on-line estimating of the unknown system parameters and stabilizing the closed-loop system. To cope with actuator saturation, another robust adaptive control is proposed for the ATO system, by explicitly considering the actuator saturation nonlinearity other than unknown system parameters, which is also proved capable of stabilizing the closed-loop system. Simulation results are presented to verify the effectiveness of the two proposed control laws.

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

This paper introduces a framework of parallel control and management for high-speed railway systems (HRSs). First, based on multiagent modeling, an artificial HRS that is consistent with realistic operations of the actual HRS is constructed. Then, different kinds of computational experiments are performed on the artificial HRS, followed by analysis and synthesis with a case. Finally, through an interactive and parallel operation between the actual and artificial HRSs, a set of practical control and management strategies can be achieved for the actual HRS. With the primary objective of ensuring reliability and safety of HRSs, this study could enhance the quality of services and the integrated transportability with other existing modes of transportation systems to provide appropriate recommendations and strategies for forming an overall effective comprehensive transportation system.

ACP-Based Control and Management of Urban Rail Transportation Systems

Urban rail transportation (URT) has long become the preferred public transportation choice for major metropolitan areas such as New York, London, Paris, Moscow, Tokyo, and Beijing. The highest daily record for Beijings URT reached 5.71 million passenger trips in 2010, which makes the network extremely crowded in rush hours. To accommodate the increasing demand for URT, the service frequencies have been increased tremendously. To address these safety, efficiency, and reliability issues, the paper presents a novel parallel system for URT operations that uses the concept of parallel system and computational experiments based on artificial systems (ACP). The parallel URT system can analyze and facilitate passenger-flow management, vehicle scheduling, and other operational issues while considering human-related, environmental, and other social and economical factors.

Truncated adaptation design for decentralised neural dynamic surface control of interconnected nonlinear systems under input saturation

ABSTRACT This paper studies decentralised neural adaptive control of a class of interconnected nonlinear systems, each subsystem is in the presence of input saturation and external disturbance and has independent system order. Using a novel truncated adaptation design, dynamic surface control technique and minimal-learning-parameters algorithm, the proposed method circumvents the problems of ‘explosion of complexity’ and ‘dimension curse’ that exist in the traditional backstepping design. Comparing to the methodology that neural weights are online updated in the controllers, only one scalar needs to be updated in the controllers of each subsystem when dealing with unknown systematic dynamics. Radial basis function neural networks (NNs) are used in the online approximation of unknown systematic dynamics. It is proved using Lyapunov stability theory that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. The tracking errors of each subsystems, the amplitude of NN approximation residuals and external disturbances can be attenuated to arbitrarily small by tuning proper design parameters. Simulation results are given to demonstrate the effectiveness of the proposed method.

Extended fuzzy logic controller for high speed train

In this paper, two dynamic models of high-speed train are presented, namely a single-mass (SM) model and an unit-displacement multi-particle (UDMP) model. Based on the former, a direct fuzzy logic controller is designed, and on the latter, a new fuzzy controller incorporating the implication logic is designed. Three sets of relevant numerical simulation are provided to demonstrate the effectiveness of the proposed control schemes through comparison.

Regenerative Braking Energy Utilization by Multi Train Cooperation

Regenerative braking system is widely used on subway trains, which will transmit kinetic energy of the trains to electricity. When the braking speed of a train is comparatively high, regenerative braking is prior to the mechanical braking. However, if the regenerative braking energy can not be absorbed by other trains in the same power supply section, the regenerative braking energy may lead to the voltage rising, even have to use dissipative resistance to absorb the surplus energy. The expected situation is that the regenerative braking energy is absorbed by other trains in the same power supply section as much as possible. Multi-train cooperation method is given in this paper, where the speed profile of the trains, selected to absorb the regenerative braking energy, will be partly adjusted. Typically, part of the original speed profile will be replaced by coast-accelerate-coast strategy, the objective is to make the train run as far as possible by only using the distributed regenerative energy. A case is studied based on Beijing Yizhuang Subway line, where speed profiles of two trains are adjusted to absorb the regenerative braking energy generated by a braking train at the same power supply section.

Adaptive neural control with intercepted adaptation for time-delay saturated nonlinear systems

In this paper, the adaptive neural control is proposed for a class of single-input-single-output nonlinear systems with state delay and input saturation. An intercepted adaptation approach is designed to attenuate the effect caused by the input saturation based on a constructed auxiliary system, and radial basis function neural networks are used in the online learning of unknown dynamics. Lyapunov–Krasovskii function is introduced to deal with the state delay. The proposed control scheme can guarantee semi-globally uniformly boundedness of the closed-loop system as rigorously proved by Lyapunov stability theorem. The ultimate and transient tracking errors will be confined in compact regions. The diameters of these regions can be adjusted to be arbitrarily small by tuning proper design parameters. Illustrative examples are used to demonstrate the effectiveness of the proposed control method.

Data-Fusion Techniques and Its Application

This paper mainly describes the data-fusion techniques combining the data from two independent sensor systems with the aim of improving overall system performance. The data-fusion algorithms that form the core of the system are described in detail, together with the development work being undertaken. Using simulated data generated by a software model and real data, the analysis of improving system performance is discussed in detail.

Urban Rail Emergency Response Using Pedestrian Dynamics

An urban rail-transit emergency response system is developed based on existing artificial systems by analyzing human behaviors from a pedestrian dynamics viewpoint. This enables necessary computational experiments on the systems that can ultimately lead to the establishment of a database of emergency response strategies and schemes.