DocumentCode :
2642729
Title :
Application of robust l1 fault detection and isolation to an industrial benchmark using a genetic algorithm
Author :
Curry, Tramone D. ; Collins, Emmanuel G., Jr.
Author_Institution :
Belcan Corporation, 4750 East Park Dr., Palm Beach Gardens, FL, 33410, USA
fYear :
2006
fDate :
4-6 Oct. 2006
Firstpage :
752
Lastpage :
759
Abstract :
To aid in the transition of fault detection and isolation (FDI) theory to practice, a realistic, nonlinear industrial diesel engine benchmark was defined by Blanke et al. This paper applies a robust l1 fault detection and isolation (FDI) technique to this benchmark. Using a linear model and assuming appropriate parametric uncertainty, a bank of robust linear estimators is developed using mixed structured singular value (MSSV) and l1 theories. To obtain the estimator parameters a real-coded genetic algorithm is used to solve the optimization problem. These estimators are then used to perform FDI of the industrial diesel engine actuator. The results illustrate the power of hybrid evolutionary algebraic techniques for solving important problems in estimation and control.
Keywords :
Actuators; Computer industry; Diesel engines; Electrical equipment industry; Fault detection; Genetic algorithms; Industrial control; Robustness; USA Councils; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
Conference_Location :
Munich, Germany
Print_ISBN :
0-7803-9797-5
Electronic_ISBN :
0-7803-9797-5
Type :
conf
DOI :
10.1109/CACSD-CCA-ISIC.2006.4776740
Filename :
4776740
Link To Document :
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