Open AccessMultiple operating mode ANFIS modelling for speed control of HSEMU
Author(s) -
Fu Yating,
Yang Hui,
Ding Jinliang
Publication year - 2018
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2017.0121
Subject(s) - adaptive neuro fuzzy inference system , control theory (sociology) , controller (irrigation) , electronic speed control , computer science , mode (computer interface) , traction control system , control engineering , simulation , automotive engineering , engineering , fuzzy logic , fuzzy control system , control (management) , artificial intelligence , electrical engineering , agronomy , biology , operating system
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.