报告题目：Ultimately Bounded Filtering Subject to Impulsive Measurement Outliers

报告简介：In this talk, we are concerned with the ultimately bounded filtering problem for a class of linear time-delay systems subject to norm-bounded disturbances and impulsive measurement outliers (IMOs). The considered IMOs are modeled by a sequence of impulsive signals with certain known minimum norm (i.e. the minimum of the norms of all impulsive signals). In order to characterize the occasional occurrence of IMOs, a sequence of independently and identically distributed random variables is introduced to depict the interval lengths (i.e. the durations between two adjacent IMOs) of the outliers. In order to achieve satisfactory filtering performance, a novel parameter-dependent filtering approach is proposed to protect the filtering performance from IMOs by using a special outlier detection scheme, which is developed based on a particular input-output model. First, the ultimate boundedness (in mean square) of the filtering error is investigated by using the stochastic analysis technique and Lyapunov-functional-like method. Then, the desired filter gain matrix is derived through solving a constrained optimization problem. Furthermore, the designed filtering scheme is applied to the case where the statistical properties about the interval lengths of outliers are completely unknown.

报告人：邹磊, 东华大学信息科学与技术学院特聘研究员，博导。主要从事复杂系统的状态估计与控制、测量野值下的状态估计、网络化系统的控制及滤波等相关问题的研究。

报告时间：2022年8月19日（星期五）下午4:30

报告地点：腾讯会议，ID：673-680-488

主办单位：扬州大学数学科学学院

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