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

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• 作者：Yating Fu^a ; ^b ; Hui Yang ; ^a ; ^b ; ^{yhshuo@263.net" class="auth_mail" title="E-mail the corresponding author} ; Dianhui Wang^c ; ^a
• 关键词：High-speed electric multiple unit ; Speed tracking ; Generalized predictive control ; Computational intelligence
• 刊名：Information Sciences
• 出版年：2017
• 出版时间：10 January 2017
• 年：2017
• 卷：376
• 期：Complete
• 页码：202-215
• 全文大小：1143 K

文摘

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.