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Robust fault estimation based on zonotopic Kalman filter for discrete‐time descriptor systems
Author(s) -
Wang Ye,
Puig Vicenç,
Cembrano Gabriela
Publication year - 2018
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4298
Subject(s) - control theory (sociology) , robustness (evolution) , kalman filter , filter (signal processing) , computer science , parameterized complexity , bounded function , fault detection and isolation , actuator , discrete time and continuous time , mathematics , algorithm , artificial intelligence , statistics , control (management) , chemistry , computer vision , gene , mathematical analysis , biochemistry
Summary This paper proposes a set‐based approach for robust fault estimation of discrete‐time descriptor systems. The considered descriptor systems are subject to unknown‐but‐bounded uncertainties (state disturbances and measurement noise) in predefined zonotopes and additive actuator faults. The zonotopic fault estimation filter for descriptor systems is built based on fault detectability indices and matrix to estimate fault magnitude in a deterministic set. The zonotopic fault estimation filter gain is designed in a parameterized form. Within a set‐based framework, following the zonotopic Kalman filter, the optimal filter gain is computed by minimizing the size of the corresponding zonotopes to achieve robustness against uncertainties and the identification of occurred actuator faults. Besides, boundedness of the proposed zonotopic fault estimation is analyzed, which proves that the size of obtained fault estimation bounds is not growing in time. Finally, the simulation results with two application examples are provided to show the effectiveness of the proposed approach.