Identification for passive robust fault detection using zonotope-based set-membership approaches
Rights accessOpen Access
In this paper, the problem of identification for passive robust fault detection, when a bounded description of the modelling uncertainty is considered, is addressed. Two set-membership identification methods are introduced to address this problem: the interval predictor and bounded error approaches. These two identification approaches naturally lead to two robust fault detection tests: the direct and inverse tests, respectively, which are also introduced and discussed. Implementation algorithms make use of a zonotope to approximate the parameter uncertainty set. Moreover, underlying hypothesis of both approaches is discussed and applicability conditions are stated. A case study based on a four-tank system is used to illustrate the applicability and the properties of the two identification approaches as well as the corresponding fault detection
CitationBlesa, J.; Puig, V.; Saludes, J. Identification for passive robust fault detection using zonotope-based set-membership approaches. "International journal of adaptive control and signal processing", Novembre 2011, vol. 25, núm. 9, p. 788-812.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder