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...

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Main Authors: Guang He, Jie Li, Peng Cui, Yun Li
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
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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
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AT jieli tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain
AT pengcui tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain
AT yunli tsfuzzymodelbasedcontrolstrategyforthenetworkedsuspensioncontrolsystemofmaglevtrain
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