具有非线性扰动的网络控制系统的鲁棒稳定化

针对一类具有随机时延和非线性扰动的网络控制系统,利用变采样周期的方法,将连续被控对象离散化,使网络控制系统建模为部分转移概率未知的非线性Markov跳变系统.通过随机Lyapunov方法,给出保证整个闭环系统随机稳定的充分条件,同时得到非线性扰动项的最大界.仿真算例表明了所提出方法的有效性.

Robust stabilization of networked control systems with nonlinear perturbation

For a class of networked control systems with random delay and nonlinear perturbation, by applying variableperiod
sampling method, the discretization of networked control systems is modeled as a nonlinear Markovian jump systems
with partly unknown transition probabilities. By means of the stochastic Lyapunov method, a sufficient condition is presented,
which guarantees the stochastical stability of the closed-loop system and at the same time maximizes the bound on the nonlinearity.
A simulation example is presented to illustrate the effectiveness of the proposed method.