In this paper, sampled-data control is proposed to stabilize the nonlinear system, which is expressed as a Takagi-Sugeno (T-S) fuzzy submodels. Based on suitable Lyapunov- Krasovskii functional (LKF) along with new weighted integral inequalities, the sufficient conditions are derived in terms of linear matrix inequalities, which ensure the exponential stability of the proposed closed loop T-S fuzzy system. The peculiarity of this paper is: as novel integral inequalities and LKF are proposed, less conservative results are provided when compared to existing results. Besides that, wind energy conversion systems, chaotic systems, and an inverted pendulum are validated with derived sufficient conditions. The corresponding simulation results show the merit of the proposed results over the existing works.

中文翻译：

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非线性系统鲁棒采样数据模糊控制及其应用：自由权矩阵法


在本文中，提出了采样数据控制来稳定非线性系统，其表示为 Takagi-Sugeno (TS) 模糊子模型。基于合适的Lyapunov-Krasovskii泛函（LKF）以及新的加权积分不等式，根据线性矩阵不等式推导了充分条件，这确保了所提出的闭环TS模糊系统的指数稳定性。本文的特点是：由于提出了新的积分不等式和 LKF，与现有结果相比，提供了不太保守的结果。除此之外，风能转换系统、混沌系统和倒立摆也通过导出的充分条件进行了验证。相应的仿真结果表明了所提出的结果相对于现有工作的优点。