首页|${cal H}_{infty}$ Model Reduction of Takagi–Sugeno Fuzzy Stochastic Systems
${cal H}_{infty}$ Model Reduction of Takagi–Sugeno Fuzzy Stochastic Systems
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
IEEE
This paper is concerned with the problem of ${cal H}_{infty}$ 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 ${cal H}_{infty}$ 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.
${cal H}_{infty}$ model reductionCone complementary linearizationTakagi–Sugeno (T–S) fuzzy systemsstochastic systems
Su, X.、Wu, L.、Shi, P.、Song, Y.-D.
展开 >
Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, China
NETL
NSTL
IEEE
