一类存在数据丢失二维离散系统的H∞滤波
H-infinity filtering for a class of two-dimensional discrete systems with data dropouts

研究输出测量数据丢失情况下二维线性离散系统的H∞滤波问题. 首先, 将数据丢失现象描述为随机伯努 利序列, 在此基础上建立二维系统状态估计误差的随机动态方程. 其次, 定义随机意义下的二维系统均方渐近稳定 性和H∞性能, 基于线性矩阵不等式给出误差系统满足均方渐近稳定和H∞性能的一个充分条件, 该条件可以实现 滤波器参数矩阵的设计. 同时, 研究结果被进一步推广到不确定二维系统. 最后, 通过仿真示例验证了理论结果的有 效性.
This paper considers the H-infinity filtering problem of 2-D discrete linear systems with output measurement dropouts. Firstly, data dropout is modeled by a stochastic Bernoulli sequence, and then the stochastic dynamic equation of state estimation error is established. Secondly, the mean-square asymptotically stable and H-infinity performance of 2-D systems are defined. A sufficient condition is given in terms of linear matrix inequalities, which guarantees the error system to be mean-square asymptotically stable and has H-infinity performance. The condition can also realize the design of the filter matrix parameters. Then, the result is also extended to the 2-D systems with uncertain parameters. Finally, the effectiveness of the theoretical result is validated by a numerical example.