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.
引用
收藏
页码：202 / 215
页数：14
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