Finite-time filtering for fuzzy nonlinear semi-Markov jump systems with deception attacks and aperiodical transmission

This paper investigates finite-time event-triggered filtering problems for fuzzy nonlinear semi-Markov jump systems (S-MJSs) subject to deception attacks. First, an interval type-2 (IT2) fuzzy S-MJSs is presented that can capture parameter uncertainties, in which the stochastic behavior is described by semi-Markov process while the sojourn-time obeys non-exponential distribution. Second, we design an adaptive event-triggered mechanism (AETM) for IT2 fuzzy S-MJSs that can save network resources, in which the triggered parameter can be automatically adjusted with the error information rather than a fixed value. Third, a hidden-Markov model is employed to represent the asynchronous situation between the filter and system. Then, a new IT2 fuzzy filtering error system is modeled by taking the effects of random deception attacks and AETM into consideration. Moreover, finite-time boundedness (FTB) analysis and a filter design method are proposed. Finally, an example is given to verify the effectiveness of the finite-time event-triggered filtering algorithm.(c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Automated summary

This paper investigates finite-time event-triggered filtering problems for fuzzy nonlinear semi-Markov jump systems subject to deception attacks. An interval type-2 fuzzy S-MJSs is presented to capture parameter uncertainties. An adaptive event-triggered mechanism is designed to save network resources. Finite-time boundedness analysis and a filter design method are proposed.