Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/77924
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: H∞ model reduction of Takagi-Sugeno fuzzy stochastic systems
Other Titles: H infinity model reduction of Takagi-Sugeno fuzzy stochastic systems
Author: Su, X.
Wu, L.
Shi, P.
Song, Y.
Citation: IEEE Transactions on Cybernetics, 2012; 42(6):1574-1585
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2012
ISSN: 1083-4419
1941-0492
Statement of
Responsibility: 
Xiaojie Su, Ligang Wu, Peng Shi and Yong-Duan Song
Abstract: This paper is concerned with the problem of H(∞) model reduction for Takagi-Sugeno (T-S) fuzzy stochastic systems. For a given mean-square stable T-S fuzzy stochastic system, our attention is focused on the construction of a reduced-order model, which not only approximates the original system well with an H(∞) performance but also translates it into a linear lower dimensional system. Then, the model reduction is converted into a convex optimization problem by using a linearization procedure, and a projection approach is also presented, which casts the model reduction into a sequential minimization problem subject to linear matrix inequality constraints by employing the cone complementary linearization algorithm. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed methods.
Keywords: Cone complementary linearization, H∞ model reduction, stochastic systems, Takagi–Sugeno (T–S) fuzzy systems.Discrete-time systems
fault estimation (FE)
piecewise Lyapunov functions
Takagi–Sugeno (T–S) fuzzy models.
Rights: © 2012 IEEE
DOI: 10.1109/TSMCB.2012.2195723
Appears in Collections:Aurora harvest 4
Electrical and Electronic Engineering publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.