Open AccessFault estimation for continuous‐time Markovian jump systems by a mode‐dependent intermediate estimator
Author(s) -
Wang Guoliang,
Yi Chenglong,
Shen Mouquan
Publication year - 2018
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.2017.1293
Subject(s) - estimator , mode (computer interface) , control theory (sociology) , jump , fault (geology) , computer science , variable (mathematics) , estimation , state (computer science) , markov process , random variable , state variable , mathematics , algorithm , engineering , control (management) , statistics , artificial intelligence , mathematical analysis , physics , systems engineering , quantum mechanics , seismology , thermodynamics , geology , operating system
This study focuses on the fault estimation problem for a class of continuous‐time Markovian jump systems. A kind of fault estimation approach is proposed, and the established intermediate estimator could estimate the state and fault simultaneously. Particularly, a stochastically intermediate variable depending on operation modes is firstly introduced. Meanwhile, another kind of intermediate variable is constructed by a series of mode‐dependent parameters and its probability distribution. Different from the former one, it is independent of system mode and does not need its operation mode available online. Compared with some existing fault estimation methods, the proposed algorithms could bear stochastic failure and have less conservatism. Two practical examples are exploited to demonstrate the effectiveness and superiority of the proposed methods.