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期刊论文
H∞ Model Reduction of Takagi–Sugeno Fuzzy Stochastic Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics),2012,42(6):1574 - 158 | 2012年05月18日 | 10.1109/TSMCB.2012.2195723
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.
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