Open AccessNon‐fragile H ∞ filtering for large‐scale power systems with sensor networks
Author(s) -
Zhang Liangliang,
Zhang Hongbin,
Ding Xuan
Publication year - 2017
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.0988
Subject(s) - control theory (sociology) , filter (signal processing) , set (abstract data type) , computer science , scale (ratio) , filtering problem , construct (python library) , state (computer science) , stability theory , control (management) , algorithm , nonlinear system , filter design , artificial intelligence , computer vision , programming language , physics , quantum mechanics
In this study, the authors investigate the non‐fragile H ∞ filtering for large‐scale power systems with sensor networks to estimate the state of each subsystem and send the states to different sites. First, for the purpose of enhancing monitoring efficiency, each sensor measures the corresponding subsystem, which can avoid the paralysis of the entire monitoring system caused by the damage of a sensor. Second, they construct the non‐fragile filter to adapt the uncertain environment. Sufficient conditions are obtained to ensure that the filtering error system is asymptotically stable with a prescribed H ∞ performance level based on the robust control approach. The filter parameters are determined by solving a set of linear matrix inequalities. A simulation example, which shows the efficiency of the proposed methods is included in this study.