Adaptive observer for fault diagnosis in nonlinear discrete-time systems

Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME

Volumn 130, Issue 2, 2008, Pages 0210051-02100510

  Caccavale, F ^a   Pierri, F ^a   Villani, L ^b  

^a UNIVERSITY OF BASILICATA   (Italy)

^b UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

Adaptive estimation; Fault diagnosis; Nonlinear systems

Indexed keywords

ADAPTIVE SYSTEMS; CONTINUOUS TIME SYSTEMS; DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; FORECASTING; HEALTH; INDUSTRIAL ROBOTS; NONLINEAR SYSTEMS; PARAMETER ESTIMATION; ROBOT APPLICATIONS; SYSTEM STABILITY;

ADAPTIVE OBSERVER (AO); DISCRETE TIME (DT); FAULT DIAGNOSIS (FD); FAULT EFFECTS; FAULT ISOLATION; GLOBAL EXPONENTIAL STABILITY (GES); NONLINEAR DISCRETE-TIME SYSTEMS; OBSERVER (OBS); PARAMETRIC MODELING; ROBOT MANIPULATORS; STATE PREDICTION;

ELECTRIC FAULT CURRENTS;

EID: 47049131455     PISSN: 00220434     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.2837310     Document Type: Article

References (26)

1. Chen, J., and Patton, R. J., 1999, Robust Model Based Fault Diagnosis for Dynamic Systems, Kluwer Academic Publishers, Dordrecht.
2. Frank, P. M., 1990, "Fault Diagnosis in Dynamic Systems Using Analytical and Knowledge-Based Redudancy - A Survey and Some New Results," Automatica, 26, pp. 459-474.
3. Frank, P. M., 1996, "Analytical and Qualitative Model-Based Fault Diagnosis - A Survey and Some New Results," Eur. J. Control, 2, pp. 6-28.
4. Gertler, J., 1998, Fault Detection and Diagnosis in Engineering Systems, Marcel Dekker, New York.
5. Patton, R. J., Frank, P. M., and Clark, R. N., 2000, Issues in Fault Diagnosis for Dynamic Systems, Springer-Verlag, Berlin.
6. Isermann, R., and Freyermuth, B., 1991, "Process Fault Diagnosis Based on Process Model Knowledge - Part I: Principles for Fault Diagnosis Wim Parameter Estimation," ASME J. Dyn. Syst., Meas., Control, 113, pp. 620-626.
7. Isermann, R., and Freyermuth, B., 1991, "Process Fault Diagnosis Based on Process Model Knowledge - Part H: Case Study, Experiment," ASME J. Dyn. Syst., Meas., Control, 113, pp. 627-633.
8. De Persis, C., and Isidori, A., 2001, "A geometric Approach to Nonlinear Fault Detection and Isolation," IEEE Trans. Autom. Control, 46, pp. 853-865.
9. Mattone, R., and De Luca, A., 2006, "Relaxed Fault Detection and Isolation: An Application to a Nonlinear Case Study," Automatica, 42, pp. 109-116.
10. Demetriou, M. A., and Polycarpou, M. M., 1998, "Incipient Fault Diagnosis of Dynamical Systems Using Online Approximators," IEEE Trans. Autom. Control, 43, pp. 1612-1617.
11. Polycarpou, M. M., and Helmicki, A. J., 1995, "Automated Fault Detection and Accomodation: A Learning Systems Approach," IEEE Trans. Syst. Man Cybern., 25, pp. 1447-1458.
12. Trunov, A. B., and Polycarpou, M. M., 2000, "Automated Fault Diagnosis in Nonlinear Multivariable Systems Using a Learning Methodology," IEEE Trans. Neural Netw., 11, pp. 91-101.
13. Vemuri, A., and Polycarpou, M. M., 1996, "Robust Nonlinear Fault Diagnosis in Input-Output Systems," Int. J. Control, 68, pp. 343-360.
14. Vemuri, A. T., 2001, "Sensor Bias Fault Diagnosis in a Class of Nonlinear Systems," IEEE Trans. Autom. Control, 46, pp. 949-954.
15. Zhang, X., Polycarpou, M. M., and Parisini, T., 2002, "A Robust Detection and Isolation Scheme for Abrupt and Incipient Faults in Nonlinear Systems," IEEE Trans. Autom. Control, 47, pp. 576-593.
16. Xu, A., and Zhang, Q., 2004, "Residual Generation for Fault Diagnosis in Linear Time-Varying Systems," IEEE Trans. Autom. Control, 49, pp. 767-772.
17. Caccavale, F., and Villani, L., 2004, "An Adaptive Observer for Fault Diagnosis in Nonlinear Discrete-Time Systems," Proceedings of the 2004 American Control Conference, IEEE, Piscataway, NJ, pp. 2463-2468.
18. Caccavale, F., and Villani, L., 2002, "Fault Diagnosis for Industrial Robots," Fault Diagnosis and Fault Tolerance for Mechatronic Systems: Recent Advances, Caccavale, F., and Villani, L., eds., Springer-Verlag, Berlin.
19. Patton, R. J., Uppal, F. J., and Lopez-Toribio, C. J., 2001, "Soft Computing Approaches to Fault Diagnosis for Dynamic Systems: A Survey," Preprints of the 4th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, Budapest, pp. 298-311.
20. de Vahl Davis, G., 1986, Numerical Methods in Engineering and Science, Allen & Unwin, London.
21. Funahashi, K., 1989, "On the Approximate Realization of Continuous Mappings by Neural Networks," Neural Networks, 2, pp. 183-192.
22. Haykin, S., 1998, Neural Networks: A Comprehensive Foundation, Prentice Hall, Englewood Cliffs, NJ.
23. Åström, K. J., and Wittenmark, B., 1995, Adaptive Control, 2nd ed., Addison-Wesley, Reading, MA.
24. Khalil, H. K., 1996, Nonlinear Systems, 2nd ed., Prentice Hall, Englewood Cliffs, NJ.
25. Antonelli, G., Caccavale, F., and Chiacchio, P., 1999 "A Systematic Procedure for the Identification of Dynamic Parameters of Robot Manipulators," Robotica, 17, pp. 427-435.
26. Antonelli, G., Caccavale, F., Sansone, C., and Villani, L., 2004 "Fault Diagnosis for AUVs Using Support Vector Machines," Proceedings of the 2004 IEEE International Conference on Robotics and Automation, New Orleans, IEEE, New York, pp. 4486-4491.