A resilient outlier-resistant recursive filtering approach to time-delayed spatial–temporal systems with energy harvesting sensors. (August 2022) - Sun, Jie; Shen, Bo; Liu, Yufei
Abstract: This paper is concerned with a resilient outlier-resistant recursive filtering problem for a class of time-delayed spatial–temporal systems (STSs) with energy harvesting sensors. We consider a situation that the sensors are able to harvest energy from external environments and consume certain energy when the measurements are transmitted to filters. When the energy of the sensor is insufficient to maintain the normal communication between the sensors and the filters, the measurement will be regarded as missing. For the sake of obtaining a satisfactory filtering performance, the innovations influenced by the measurement outliers is constrained by introducing a saturation function in the filter. Furthermore, the resilient issue of the designed recursive filter is considered to resist the fluctuations of the filter parameters. Under the effects of sensor energy constraints, measurement outliers as well as parameter fluctuations, a resilient outlier-resistant recursive filter is designed where an upper bound (UB) is first obtained on the filtering error covariance (FEC). Then, by resorting to a matrix recursive equation, such a UB is minimized by the filter gain matrix. Finally, we exhibit a numerical example to verify the effectiveness of the proposed resilient outlier-resistant recursive filter scheme for time-delayed STSs. Highlights: The sensor energy-constrained phenomenon is taken into account. The influence from measurement outliers is considered in spatial-temporal systems. A resilient recursive algorithm is proposed to design appropriate filter.