Robust sampled-data control with random missing data scenario
Robust sampled-data control with random missing data scenario
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DOI：
10.1080/00207179.2014.896476
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发表时间：
2014-02
影响因子：
2.1
通讯作者：
Tae H. Lee;Ju H. Park;Sangmoon Lee;O. Kwon
中科院分区：
文献类型：
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作者：
Tae H. Lee;Ju H. Park;Sangmoon Lee;O. Kwon
研究了存在缺失数据的不确定动态系统的鲁棒采样控制问题。利用随机变量服从Bernoulli分布的白色序列对缺失数据进行建模，沿着时变范数有界的不确定性，以及采样系统的输入时滞方法，针对连续缺失数据情形，提出了两种采样控制系统模型.此外，当数据丢失时，控制信号被保持为最后接收的数据。以线性矩阵不等式的形式给出了期望鲁棒采样控制器存在的充分条件。最后给出了一个数值例子来说明所提出方法的有效性，并比较了两种采样控制系统模型的结果。
The problem of robust sampled-data control for uncertain dynamic systems in the presence of missing data has been investigated. By using stochastic variables with a Bernoulli distributed white sequence to model missing data, along with time-varying norm-bounded uncertainties, and the input delay approach for sampled-data systems, two models for the considered sampled-data control system are proposed as the consecutive missing data scenario. Moreover, when data are missing, the control signals are held as the last received data. Sufficient conditions for the existence of desired robust sampled-data controllers are presented in the form of a linear matrix inequality. A numerical example is given to illustrate the validity of the proposed methods and to compare the results between the two proposed models of the sampled-data control system.