Robust fault detection and diagnosis for multiple-model systems with uncertainties
MetadataShow full item record
© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.In this paper, a robust fault detection and diagnosis (FDD) method is proposed for multiple-model systems with modeling uncertainties. A compensation step is introduced to modify the mixed states and their variances obtained through the interacting multiple model (IMM) approximation and to solve the uncertainty problem. The degree of compensation is governed by a modification parameter determined by the orthogonality principle, which means that the estimation error calculated in the sub-filter using the true system models should be orthogonal to the residual error vector. To avoid over compensation in the unmatched models, a minimization procedure is used to derive the overall modification parameter. When the modification parameter is equal to one, the proposed method reduces to the IMM algorithm. An experiment is conducted through the ball and tube system to demonstrate the effectiveness of the proposed method.
Showing items related by title, author, creator and subject.
Besa, Bunda (2010)The decline is a major excavation in metalliferous mining since it provides the main means of access to the underground and serves as a haulage route for underground trucks. However, conventional mining of the decline to ...
Fulton, B.; Jones, Tod; Boschetti, F.; Sporcic, M.; De La Mare, W.; Syme, Geoffrey; Dzidic, Peta; Gorton, R.; Little, L.; Dambacher, G.; Chapman, K. (2011)We describe the different types of models we used as part of an effort to inform policy-making aiming at the management of the Ningaloo coast in the Gascoyne region, Western Australia. This provides an overview of how ...
Coll, Richard K. (1999)The research reported in this thesis comprised a cross-age inquiry of learners' mental models for chemical bonding. Learners were chosen purposefully from three academic levels-senior secondary school (Year-13, age range ...