Ultimately Bounded Filtering for Time-Delayed Nonlinear Stochastic Systems with Uniform Quantizations under Random Access Protocol

Abstract

This paper investigates the ultimately bounded filtering problem for a kind of time-delay nonlinear stochastic systems with random access protocol (RAP) and uniform quantization effects (UQEs). In order to reduce the occurrence of data conflicts, the RAP is employed to regulate the information transmissions over the shared communication channel. The scheduling behavior of the RAP is characterized by a Markov chain with known transition probabilities. On the other hand, the measurement outputs are quantized by the uniform quantizer before being transmitted via the communication channel. The objective of this paper is to devise a nonlinear filter such that, in the simultaneous presence of RAP and UQEs, the filtering error dynamics is exponentially ultimately bounded in mean square (EUBMS). By resorting to the stochastic analysis technique and the Lyapunov stability theory, sufficient conditions are obtained under which the desired nonlinear filter exists, and then the filter design algorithm is presented. At last, two simulation examples are given to validate the proposed filtering strategy.

Distributed cubature Kalman filtering for nonlinear systems with stochastic communication protocol

“…Different from the above two protocols, the characteristic of SCP is that each node is assigned the access privilege in a random way. The distributed KF issue under SCP has been done in Guo et al [26] for sensor networks. To date, there are few research results on the DCKF problem for sensor networks, not to mention the case when the SCP is considered to schedule neighboring nodes.…”

Iterative Algorithm for Parameterization of Two-Region Piecewise Uniform Quantizer for the Laplacian Source

“…It is well known that a nonuniform quantizer model, well accommodated to the signal's amplitude dynamic and a nonuniform pdf, has lower quantization error compared to the uniform quantizer (UQ) model with an equal number of quantization levels or equal bit-rates [2,11,13,18,[20][21][22][23][24][25][26][27]. However, due to the fact that UQ is the simplest quantizer model, it has been intensively studied, for instance in [23,24,[28][29][30][31][32]. Moreover, the high complexity of nonuniform quantizers can outweigh the potential performance advantages over uniform quantizers [21].…”