Asynchronous Partially Mode-Dependent Filtering of Network-Based MSRSNSs With Quantized Measurement

This article addresses the issue of asynchronous partially mode-dependent filtering for networked Markov switching repeated scalar nonlinear systems (MSRSNSs) subject to quantized measurements (QMs). Especially, a novel partially mode-dependent filter (PMDF) is constructed, where the signal transmission of a filter mode occurred randomly and is modeled by a Bernoulli distributed sequence. The designed PMDF is different from state mode, which is governed by an asynchronous switching rule. By utilizing a diagonally dominant-type Lyapunov functional (DDTLF), sufficient conditions ensure that the existence of the PMDF and the ℓ 2 -l ∞ performance index are derived. Finally, an economic example is adopted to substantiate the applicability of the developed theoretical results.