Multiple operating mode ANFIS modelling for speed control of HSEMU. Issue 1 (17th October 2017)

• Record Type: Journal Article
• Authors: Fu, Yating; Yang, Hui; Ding, Jinliang
• Is Part Of: IET intelligent transport systems. Volume 12:Issue 1(2018)
• Page Start: 31
• Page End: 40
• Publication Date: 2017-10-17
• Subjects: rail traffic control -- adaptive control -- fuzzy neural nets -- fuzzy reasoning -- nonlinear control systems -- velocity control -- stability -- closed loop systems -- neurocontrollers -- large‐scale systems -- control system synthesis; multiple operating mode ANFIS modelling -- speed control -- HSEMU -- high‐speed electric multiple unit -- complex nonlinear system -- traction mode -- braking mode -- coasting mode -- traffic density -- high‐speed railway -- multiple OM running model -- nonlinear relationship -- running speed -- controlling force -- adaptive neuro‐fuzzy inference system -- nonlinear modelling -- MOM‐ANFIS model -- speed controller -- OM selection mechanism design -- stability analysis -- closed‐loop system; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2017.0121
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : High‐speed electric multiple unit (HSEMU) is a complex non‐linear system which runs under three typical operating modes (OMs) including traction, braking, and coasting. With the increasing traffic density of the high‐speed railway, the conventionally manual control strategies may be inapplicable for the HSEMU to maintain a good running performance. To enhance the running performances, in this study, a novel multiple OM (MOM) running model is designed to accurately describe the non‐linear relationship between running speed and controlling force. By utilising the advantages of adaptive neuro‐fuzzy inference system (ANFIS) on non‐linear modelling, this study proposes an MOM‐ANFIS model of HSEMU. On the basis of the established MOM‐ANFIS model, a new speed controller incorporated with OM selection mechanism is designed to achieve speed control of HSEMU followed by a stability analysis of the closed‐loop system. Comparative experimental results using practical running data show that the proposed MOM‐ANFIS model displays better modelling accuracy and the corresponding control strategy achieves improved speed control performances for the HSEMU.