Ultimately Bounded State Estimation for Nonlinear Networked Systems With Constrained Average Bit Rate: A Buffer-Aided Strategy - Sun, Jie; Shen, Bo; Zou, Lei (IEEE transactions on signal processing, 2024)
This article investigates the state estimation issue for a nonlinear networked system with network-based communication, where the measurement signals of the system are transmitted in an intermittent manner under the effects of unreliable communication. For the sake of enhancing the utilization efficiency of measurement signals, a buffer-aided strategy is employed here by storing historical measurement signals when the communication channel is unavailable. A so-called average bit rate constraint is introduced to restrain the transmission rate of the communication channel with the aim of avoiding the communication burden. The essential objective of this article is to construct a state estimator for the nonlinear system subject to the effects of intermittent signal transmissions and buffer-aided strategy. By using the Lyapunov-function-based method and the stochastic analysis technique, a sufficient condition is obtained for the exponentially ultimate boundedness of the estimation error dynamics under the average bit rate constraint. Then, by using a constrained optimization problem, the desired estimator gain matrix is derived. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed estimation method.