Real-time optimal control of tracking running for high-speed electric multiple unit

被引：7
作者：
Fu, Yating [1 ,2 ]
Yang, Hui [1 ,2 ]
Wang, Dianhui [1 ,3 ]
机构：
[1] East China Jiaotong Univ, Sch Elect & Elect Engn, Nanchang 330013, Jiangxi, Peoples R China
[2] Key Lab Adv Control & Optimizat Jiangxi Prov, Nanchang 330013, Jiangxi, Peoples R China
[3] La Trobe Univ, Dept Comp Sci & Informat Technol, Melbourne, Vic 3086, Australia
来源：
INFORMATION SCIENCES | 2017年 / 376卷
基金：
中国国家自然科学基金;
关键词：
High-speed electric multiple unit; Speed tracking; Generalized predictive control; Computational intelligence; PREDICTIVE CONTROL; ANFIS MODEL; SYSTEMS; TRAIN; OPTIMIZATION; ALGORITHM; NETWORK;
D O I：
10.1016/j.ins.2016.10.024
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
High-speed electric multiple unit (HSEMU) is an advanced transportation system, which share some special characteristics such as nonlinear dynamics, complex working environment and time-varying operational conditions. To achieve a safe, punctual and automatic running of HSEMU, effective modeling methods of HSEMU and real-time optimal control schemes are useful to further improve the running performances. This paper aims to develop intelligent control techniques for speed tracking control of HSEMU. The well-known adaptive neuro-fuzzy inference system (ANFIS) is employed to model the dynamics, and an ANFIS-based generalized predictive controller is proposed with a stability analysis of the closed-loop system. Experimental results with comparisons on real-world running data demonstrate that our proposed techniques in this work can perform favorably in terms of both safety and punctuality. (C) 2016 Elsevier Inc. All rights reserved.
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页码：202 / 215
页数：14
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