This paper addresses the stability and stabilization problems of uncertain Takagi–Sugeno (T-S) fuzzy system with control packet dropout. The process of packet loss is proposed, which is modeled according to some white noise sequences of Bernoulli distribution. Then, under the zero-input strategy, a newly stochastic switched sampled-data controller is introduced. Based on the Lyapunov function method, a novel Lyapunov–Krasovskii (LKF) function is constructed via introducing a fuzzy membership functions (FMFs), which can use the information about the actual sampling pattern. Each term of the LKF need not be positive, but it needs to be positive at sampling instants. Using the reciprocally convex method and relaxed free-matrix-based (FMB) integral inequality, novel stabilization criteria are established to guarantee that the T-S fuzzy system is stochastic stable when the control packet dropout occurs in a random way. Based on the linear matrix inequalities (LMIs), a fuzzy controller design algorithm for sampled data is presented to obtain a larger sampling interval. Finally, two numerical examples are used to verify the effectiveness and advantages of the proposed method.

本文针对具有控制数据包丢失的不确定Takagi-Sugeno（TS）模糊系统的稳定性和镇定问题。提出了丢包过程，并根据伯努利分布的一些白噪声序列进行了建模。然后，在零输入策略下，引入了一种新的随机切换采样数据控制器。基于Lyapunov函数方法，通过引入模糊隶属函数（FMF）构造了一个新颖的Lyapunov–Krasovskii（LKF）函数，该函数可以使用有关实际采样模式的信息。LKF的每个项不必为正，但在采样瞬间必须为正。使用双向凸方法和基于自由矩阵的（FMB）积分不等式，建立了新的稳定准则，以保证当控制数据包丢失以随机方式发生时，TS模糊系统是随机稳定的。基于线性矩阵不等式（LMI），提出了一种模糊控制器设计的采样数据算法，以获取更大的采样间隔。最后，通过两个数值例子验证了所提方法的有效性和优越性。