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Unknown input modeling and robust fault diagnosis using black box observers

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Title Unknown input modeling and robust fault diagnosis using black box observers
 
Creator MANUJA, SEEMA
NARASIMHAN, SHANKAR
PATWARDHAN, SC
 
Subject actuators
control theory
electric fault currents
failure analysis
 
Description A key issue that needs to be addressed while performing fault diagnosis using black box models is that of robustness against abrupt changes in unknown inputs. A fundamental difficulty with the robust FDI design approaches available in the literature is that they require some a priori knowledge of the model for unmeasured disturbances or modeling uncertainty. In this work, we propose a novel approach for modeling abrupt changes in unmeasured disturbances when innovation form of state space model (i.e. black box observer) is used for fault diagnosis. A disturbance coupling matrix is developed using singular value decomposition of the extended observability matrix and further used to formulate a robust fault diagnosis scheme based on generalized likelihood ratio test. The proposed modeling approach does not require any a priori knowledge of how these faults affect the system dynamics. To isolate sensor and actuator biases from step jumps in unmeasured disturbances, a statistically rigorous method is developed for distinguishing between faults modeled using different number of parameters. Simulation studies on a heavy oil fractionator example show that the proposed FDI methodology based on identified models can be used to effectively distinguish between sensor biases, actuator biases and other soft faults caused by changes in unmeasured disturbance variables. The fault tolerant control scheme, which makes use of the proposed robust FDI methodology, gives significantly better control performance than conventional controllers when soft faults occur. The experimental evaluation of the proposed FDI methodology on a laboratory scale stirred tank temperature control set-up corroborates these conclusions.
 
Publisher Elsevier
 
Date 2009-09-12T08:34:01Z
2011-11-25T15:21:37Z
2011-12-26T13:04:44Z
2011-12-27T05:50:44Z
2009-09-12T08:34:01Z
2011-11-25T15:21:37Z
2011-12-26T13:04:44Z
2011-12-27T05:50:44Z
2009
 
Type Article
 
Identifier Journal of Process Control 19(1), 25-37
0959-1524
http://dx.doi.org/10.1016/j.jprocont.2008.02.004
http://hdl.handle.net/10054/1629
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1629
 
Language en