T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train
The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S) fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters un...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2015-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/291702 |
id |
doaj-a137c888565c4dae99b753a2433218a5 |
---|---|
record_format |
Article |
spelling |
doaj-a137c888565c4dae99b753a2433218a52020-11-24T21:24:40ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/291702291702T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev TrainGuang He0Jie Li1Peng Cui2Yun Li3College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, ChinaCollege of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, ChinaCollege of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, ChinaCollege of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, ChinaThe control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S) fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.http://dx.doi.org/10.1155/2015/291702 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Guang He Jie Li Peng Cui Yun Li |
spellingShingle |
Guang He Jie Li Peng Cui Yun Li T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train Mathematical Problems in Engineering |
author_facet |
Guang He Jie Li Peng Cui Yun Li |
author_sort |
Guang He |
title |
T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train |
title_short |
T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train |
title_full |
T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train |
title_fullStr |
T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train |
title_full_unstemmed |
T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train |
title_sort |
t-s fuzzy model based control strategy for the networked suspension control system of maglev train |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2015-01-01 |
description |
The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S) fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method. |
url |
http://dx.doi.org/10.1155/2015/291702 |
work_keys_str_mv |
AT guanghe tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain AT jieli tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain AT pengcui tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain AT yunli tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain |
_version_ |
1725986911974064128 |