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Distributed recursive filtering for 2-D systems with adaptive event-triggered and binary encoding schemes
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DOI：10.1080/21642583.2026.2709977.png)
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Abstract
En 中文
This paper investigates the distributed recursive filtering problem for two-dimensional (2-D) systems over sensor networks with an adaptive event-triggered scheme (ETS) and a binary encoding scheme. To alleviate the computational and communication burden, an adaptive ETS with bidirectional evolutionary properties is proposed. In addition, a binary encoding model accounting for two-dimensional time instants is developed to improve data security and facilitate the transmission of data. Within this framework, a distributed recursive filter structure that relies on the topology of the sensor networks is presented, incorporating the adaptive ETS and binary encoding scenarios. Subsequently, the 2-D mathematical induction approach is employed to derive the upper bound of the filtering error covariance (FEC), and the filter gains with satisfactory performance are obtained by minimizing the trace of the upper bound. Moreover, the boundedness criterion of FEC is developed, and the effect of triggering condition on the FEC is analyzed. Finally, the validity of the proposed distributed recursive filtering algorithm is demonstrated through the case of the heat-exchange process.
Keywords:
2-D systems
sensor networks
distributed recursive filtering
adaptive event-triggered scheme
binary encoding scheme
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