This work concentrates on addressing the sliding mode control problem of continuous-time nonlinear networked control systems. Considering the state information may not be utterly available in practice, a state observer model is designed to estimate the state information. Meanwhile, a type of discrete-time event-triggered mechanism is utilized to filter the sampled signal for reducing the occupation of network bandwidths and the transmission rate of resources. In addition, a random variable obeying the Bernoulli distribution is adopted to describe the phenomenon of uncertainties randomly occurring in the measurement. With the aid of the Lyapunov stability and sliding mode control theory, some sufficient criteria are given to both guarantee the mean-square asymptotic stability of the overall closed-loop system with an extended dissipative performance, and the reachability of predefined sliding surface. Whereafter, the event-triggered weighting matrix, and gains of sliding mode controller and with observer are obtained by solving the matrix convex optimization problem. Finally, the feasibility of the presented scheme is demonstrated through two illustrative examples.

这项工作集中于解决连续时间非线性网络控制系统的滑模控制问题。考虑到状态信息在实践中可能无法完全获得，因此设计了状态观察器模型来估计状态信息。同时，利用一种离散时间事件触发机制对采样信号进行滤波，以减少网络带宽的占用和资源的传输速率。另外，采用服从伯努利分布的随机变量来描述在测量中随机发生的不确定性现象。借助李雅普诺夫稳定性和滑模控制理论，给出了一些充分的标准，以确保具有扩展的耗散性能的整个闭环系统的均方渐近稳定性，以及预定滑动面的可达性。之后，通过解决矩阵凸优化问题，获得了事件触发的加权矩阵，滑模控制器的增益以及观察者的增益。最后，通过两个说明性实例证明了所提出方案的可行性。