Approximation-based robust adaptive automatic train control : An approach for actuator saturation

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

148 Scopus Citations
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Author(s)

  • Shigen Gao
  • Hairong Dong
  • Yao Chen
  • Bin Ning
  • Xiaoxia Yang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number6549162
Pages (from-to)1733-1742
Journal / PublicationIEEE Transactions on Intelligent Transportation Systems
Volume14
Issue number4
Online published28 Jun 2013
Publication statusPublished - Dec 2013

Abstract

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. © 2000-2011 IEEE.

Research Area(s)

  • Actuator saturation, Automatic train operation (ATO), Neural network, Robust adaptive control

Citation Format(s)

Approximation-based robust adaptive automatic train control: An approach for actuator saturation. / Gao, Shigen; Dong, Hairong; Chen, Yao et al.
In: IEEE Transactions on Intelligent Transportation Systems, Vol. 14, No. 4, 6549162, 12.2013, p. 1733-1742.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review