Open AccessHMM‐based filtering for slow‐sampling singularly perturbed jumping systems
Author(s) -
Yang Chengyu,
Xia Jianwei,
Huang Xia,
Song Xiaona,
Shen Hao,
Wang Jian
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2019.0661
Subject(s) - control theory (sociology) , filter (signal processing) , lyapunov function , asynchronous communication , computer science , hidden markov model , filter design , mathematics , lyapunov stability , artificial intelligence , telecommunications , nonlinear system , control (management) , computer vision , physics , quantum mechanics
This study concentrates on the filtering for the slow‐sampling jumping singularly perturbed systems, in which the situation that the filter mode is inconsistent with the system mode is taken into consideration. Based on the hidden‐Markov model (HMM), such an asynchronous phenomenon between the system mode and the filter mode is depicted. Additionally, the unreliable communication channel resulting in packet loss is described through the assistance of a random variable. The authors' purpose is to design a filter that ensures the error system is extended stochastically dissipative. Moreover, with the aid of the Lyapunov stability theory and linear matrix inequality approach, a set of ϵ ‐independent conditions are derived to obtain the filter gains. Eventually, the effectiveness of the proposed method is demonstrated by a numerical example and a modified tunnel diode circuit model.