Title: Modelling and control design for an electro-pneumatic braking system in trains with multiple locomotives

Authors: Jianfeng Liu; Youmei Liu; Zhiwu Huang; Weihua Gui; Huosheng Hu

Addresses: School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China. ' China South Locomotive and Rolling, Zhuzhou Electric Locomotive Co. Ltd., Zhuzhou 412001, China. ' School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China. ' School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China. ' School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK

Abstract: This paper focuses on the modelling and control design for an electro-pneumatic braking system used in multi-locomotives in order to achieve accurately and steadily braking control of heavy haul trains. To deal with various time delays, a T-S fuzzy model based on satisfaction degree is proposed to simplify the cylinder model construction and a fuzzy clustering algorithm with forgetting factors is deployed to achieve parameter self-learning in order to improve the fuzzy control accuracy. Then a fuzzy genetic algorithm is adopted as the rolling optimisation method to reduce the effect of coupling noise, system disturbance and communication random interference such that the system robustness and controller response capability are improved. The effectiveness of the proposed method is verified by simulation and practical implementations.

Keywords: electronically controlled pneumatic brakes; fuzzy genetic algorithms; model predictive control; MPC; T-S fuzzy model; modelling; control design; electro-pneumatic braking systems; heavy haul trains; train braking; multiple locomotives; braking control; clustering algorithms; parameter self-learning; fuzzy control; rolling optimisation; coupling noise; system disturbance; communication random interference.

DOI: 10.1504/IJMIC.2012.048916

International Journal of Modelling, Identification and Control, 2012 Vol.17 No.2, pp.99 - 108

Published online: 17 Dec 2014 *

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