Journal
COMPUTERS & ELECTRICAL ENGINEERING
Volume 40, Issue 7, Pages 2273-2284Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2014.08.009
Keywords
Fault detection and identification; Iterative learning algorithm; Fault tracking approximator; Time-delay systems
Categories
Funding
- Special Fund of East China University of Science and Technology for Basic Scientific Research [WH1114027, WJ1313004-1, H200-4-13192]
- National Natural Science Foundation of China [51207007, 51407078]
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In this paper, a novel fault detection and identification (FDI) scheme for time-delay systems is presented. Different from the existing FDI design methods, the proposed approach utilizes fault tracking approximator (FTA) and iterative learning algorithm to obtain estimates of the fault functions. Performance of the FTA is rigorously analyzed by investigating its stability and fault tracking sensitivity properties in the presence of slowly developing or abrupt faults for state delayed dynamic systems. A novel feature of the FTA is that it can simultaneously detect and identify the shape and magnitude of the faults. Additionally, an extension to a class of nonlinear time-delay systems is made by using nonlinear control theories. Finally, the applicability and effectiveness of the proposed FDI scheme is illustrated by a practical industrial process. (C) 2014 Elsevier Ltd. All rights reserved.
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