Dynamic Event-Triggered Resilient Filtering for Networked 2D FMLSS Systems: Tackling Bit Flips and Asynchronous Delays

Abstract

In this paper, the dynamic event-triggered filtering problem is investigated for a class of two-dimensional (2D) Fornasini-Marchesini local state-space (FMLSS) delayed systems under binary encoding-decoding schemes with probabilistic bit flips. To reduce unnecessary communications and computations in complex network systems, alleviate network energy consumption, and optimize the use of network resources, a novel dynamic event-triggered mechanism with bidirectional evolutionary characteristics is proposed. To enhance the reliability of digital communication, a binary encoding-decoding scheme is employed, considering the scenario in which transmitted binary bits may be flipped in a noisy memoryless symmetric channel. To leverage delayed decoded measurements, a measurement reconstruction approach is introduced. Subsequently, a recursive resilient filtering framework is developed to mitigate the effects of event-triggering errors, encoding errors, and bit-flip errors on filtering accuracy. The filter gain parameter is obtained by minimizing an upper bound on the filtering error covariance. Furthermore, through rigorous mathematical analysis, the monotonicity of filtering performance with respect to triggering parameters is discussed. Finally, the feasibility of the designed filtering framework is verified through a case simulation.