Bin Ning
Beijing Jiaotong University
40 Papers
302 Citations
Bin Ning is an academic researcher from Beijing Jiaotong University. The author has contributed to research in topics: Handover & Adaptive control. The author has an hindex of 17, co-authored 40 publications. Previous affiliations of Bin Ning include Carleton University.
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Papers
Automatic Train Control System Development and Simulation for High-Speed Railways
TL;DR: Numerical modeling of high-speed trains in the Chinese high- speed train system and its associate automatic control systems are described in detail and modeling and simulation of train operation systems are analyzed and demonstrated.
369
Approximation-Based Robust Adaptive Automatic Train Control: An Approach for Actuator Saturation
TL;DR: 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 with a robust adaptive law proposed, which is proved capable of on- line estimating of the unknown system parameters and stabilizing the closed-loop system.
173
Computationally Inexpensive Tracking Control of High-Speed Trains With Traction/Braking Saturation
TL;DR: A multiple point mass with a single-coordinate dynamic model that reflects resistive and transient impacts is derived, and based on this, computationally inexpensive robust adaptive control designs with optimal task distribution for speed and position tracking are proposed under traction/braking nonlinearities and saturation limitations.
152
Cross-Layer Handoff Design in MIMO-Enabled WLANs for Communication-Based Train Control (CBTC) Systems
TL;DR: This paper takes an integrated design approach to jointly optimize handoff decisions and physical layer parameters to improve the train control performance in CBTC systems and uses linear quadratic cost for the train controller as the performance measure.
138
An Introduction to Parallel Control and Management for High-Speed Railway Systems
TL;DR: A framework of parallel control and management for high-speed railway systems (HRSs) based on multiagent modeling is introduced to provide appropriate recommendations and strategies for forming an overall effective comprehensive transportation system.
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