Your browser doesn't support javascript.
loading
Adaptive slip ratio estimation for active braking control of high-speed trains.
Chen, Bin; Huang, Zhiwu; Zhang, Rui; Jiang, Fu; Liu, Weirong; Li, Heng; Wang, Jing; Peng, Jun.
Afiliação
  • Chen B; School of Automation, Central South University, Changsha 410083, China.
  • Huang Z; School of Automation, Central South University, Changsha 410083, China.
  • Zhang R; School of Automation, Central South University, Changsha 410083, China.
  • Jiang F; School of Computer Science and Engineering, Central South University, Changsha 410083, China. Electronic address: jiangfu0912@csu.edu.cn.
  • Liu W; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Li H; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Wang J; Electrical and Computer Engineering, Bradley University, Peoria, IL 61625, USA.
  • Peng J; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
ISA Trans ; 112: 302-314, 2021 Jun.
Article em En | MEDLINE | ID: mdl-33293045
ABSTRACT
Active braking control systems in high-speed trains are vital to ensure safety and are intended to reduce brake distances and prevent the wheels from locking. The slip ratio, which represents the relative difference between the wheel speed and vehicle velocity, is crucial to the design and successful implementation of active braking control systems. Slip ratio estimation and active braking control are challenging owing to the uncertainties of wheel-rail adhesion and system nonlinearities. Therefore, this paper proposes a novel adaptive slip ratio estimation approach for the active braking control based on an improved extended state observer. The extended state observer is developed through the augmentation of the system state-space to estimate the unmeasured train states as well as the model uncertainty. The accurate slip ratio is estimated using the observed extended states. Furthermore, the adaptability of the observer is improved by introducing the beetle antennae search algorithm to determine the optimal observer parameters. Finally, a feedback linearization braking control law is established to stabilize the closed-loop system due to its potential in coping with nonlinearities, which benefits the proven theoretical bounded stability. Experimental results validate the effectiveness of the proposed method.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article