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Set‐membership parity space approach for fault detection in linear uncertain dynamic systems
Author(s) -
Blesa Joaquim,
Puig Vicenç,
Saludes Jordi,
FernándezCantí Rosa M.
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2476
Subject(s) - fault detection and isolation , parity (physics) , mathematics , benchmark (surveying) , parameter space , transformation (genetics) , turbine , control theory (sociology) , set (abstract data type) , computer science , algorithm , mathematical optimization , statistics , artificial intelligence , engineering , mechanical engineering , biochemistry , physics , chemistry , control (management) , geodesy , particle physics , actuator , gene , programming language , geography
Summary In this paper, a set‐membership parity space approach for linear uncertain dynamic systems is proposed. First, a set of parity relations derived from the parity space approach is obtained by means of a transformation derived from the system characteristic polynomial. As a result of this transformation, parity relations can be expressed in regressor form. On the one hand, this facilitates the parameter estimation of those relations using a zonotopic set‐membership algorithm. On the other hand, fault detection is then based on checking, at every sample time, the non‐existence of a parameter value in the parameter uncertainty set such that the model is consistent with all the system measurements. The proposed approach is applied to two examples: a first illustrative case study based on a two‐tank system and a more realistic case study based on the wind turbine fault detection and isolation benchmark in order to evaluate its effectiveness. Copyright © 2014 John Wiley & Sons, Ltd.