LMI-based fault detection fuzzy observer design with multiple performance constraints for a class of non-linear systems: Comparative study

International Journal of Innovative Computing, Information and Control

Volumn 8, Issue 1 B, 2012, Pages 633-645

  Zhang, Dengfeng ^a   Wang, Hong ^b   Lu, Baochun ^a   Wang, Zhiquan ^a  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Fault detection; Fuzzy observer; Matrix identical transformation; Multiobjective optimization; Takagi Sugeno fuzzy model

Indexed keywords

COMPARATIVE STUDIES; FUZZY NONLINEAR SYSTEMS; FUZZY OBSERVER; IF-THEN RULES; LMI CONSTRAINTS; MATRIX; MATRIX INEQUALITY; MULTI OBJECTIVE; OBSERVER DESIGN; ON-LINE EVALUATION; PERFORMANCE CONSTRAINTS; PERFORMANCE REQUIREMENTS; TAKAGI SUGENO FUZZY MODELS; TAKAGI-SUGENO;

DESIGN; FAULT DETECTION; LINEAR TRANSFORMATIONS; MULTIOBJECTIVE OPTIMIZATION; NONLINEAR SYSTEMS;

LINEAR MATRIX INEQUALITIES;

EID: 84863034793     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (27)

1. R. Isermann and P. Balle, Trends in the application of model-based fault detection and diagnosis of technical processes, Control Engineering Practice, vol.5, no.5, pp.709-719, 1997.
2. P. M. Frank and S. X. Ding, Survey of robust residual generation and evaluation methods in observerbased fault detection systems, Journal of Process Control, vol.7, no.6, pp.403-424, 1997.
3. R. J. Patton, F. J. Uppal, S. Simani and B. Polle, Robust FDI applied to thruster faults of a satellite system, Control Engineering Practice, vol.18, no.9, pp.1093-1109, 2010.
4. S. X. Ding, Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms and Tools, Springer-Verlag, Berlin, 2008.
5. E. Sobhani-Tehrani and K. Khorasani, Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach, Springer-Verlag, London, 2009.
6. Y. Zhao, J. Lam and H. Gao, Fault detection for fuzzy systems with intermittent measurements, IEEE Transactions on Fuzzy Systems, vol.17, no.2, pp.398-410, 2009.
7. S. K. Nguang, P. Shi and S. X. Ding, Delay-dependent fault estimation for uncertain time-delay nonlinear systems: An LMI approach, Int. J. Robust Nonlinear Control, vol.16, no.18, pp.913-933, 2006.
8. M. Kowal and J. Korbicz, Fault detection under fuzzy model uncertainty, International Journal of Automation and Computing, vol.4, no.2, pp.117-124, 2007.
9. S. He and F. Liu, Fuzzy model-based fault detection for markov jump systems, Int. J. Robust and Nonlinear Control, vol.19, no.11, pp.1248-1266, 2009.
10. Z. Gao, B. Jiang, R. Qi, Y. Xu and Y. Cheng, Fuzzy observer design for near space vehicle with application to sensor fault estimation, ICIC Express Letters, vol.4, no.1, pp.177-182, 2010.
11. Z. Gao, X. Shi and S. X. Ding, Fuzzy state/disturbance observer design for T-S fuzzy systems with application to sensor fault estimation, IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, vol.38, no.3, pp.875-880, 2008.
12. Y. Zheng, H. Fang and H. O. Wang, Takagi-Sugeno fuzzy-model-based fault detection for networked control systems with Markov delays, IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, vol.36, no.4, pp.924-929, 2006.
13. Y. Wang, W. Wang and D. Wang, LMI approach to design fault detection filter for discrete-time switched systems with state delays, International Journal of Innovative Computing, Information and Control, vol.6, no.1, pp.387-398, 2010.
14. W. Chen and M. Saif, Fuzzy nonlinear unknown input observer design with fault diagnosis applications, Journal of Vibration and Control, vol.16, no.3, pp.377-401, 2010.
15. H. Yang, Y. Xia and B. Liu, Fault detection for T-S fuzzy discrete systems in finite-frequency domain, IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, vol.41, no.99, pp.1-10, 2011.
16. H. Yano, Interactive decision making for multiobjective programming problems with fuzzy domination structures, International Journal of Innovative Computing, Information and Control, vol.5, no.12(B), pp.4867-4876, 2009.
17. C. Liu, New evolutionary algorithm for multi-objective constrained optimization, ICIC Express Letters, vol.2, no.4, pp.339-344, 2008.
18. G. Feng, A survey on analysis and design of model-based fuzzy control systems, IEEE Transactions on Fuzzy Systems, vol.14, no.5, pp.676-697, 2006.
19. F. Delmotte, T. M. Guerra and A. Kruszewski, Discrete Takagi-Sugeno's fuzzy models: Reduction of the number of LMI in fuzzy control techniques, IEEE Transactions on Systems, Man, And Cybernetics-Part B: Cybernetics, vol.38, no.5, pp.1423-1427, 2008.
20. K. Tanaka, T. Hori and H. O. Wang, A multiple Lyapunov function approach to stabilization of fuzzy control systems, IEEE Transactions on Fuzzy Systems, vol.11, no.4, pp.582-589, 2003.
21. A. Sala, T. M. Guerra and R. Babuska, Perspectives of fuzzy systems and control, Fuzzy Sets and Systems, vol.156, no.3, pp.432-444, 2005.
22. C. Scherer, P. Gahinet and M. Chilali, Multiobjective output-feedback control via LMI optimization, IEEE Transactions on Automatic Control, vol.42, no.7, pp.896-911, 1997.
23. S. Boyd, L. El Ghaoui, E. Feron and V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory (Studies in Applied Mathematics), SIAM, Philadelphia, PA, USA, 1994.
24. J. Chen, C. J. Lopez-Toribio and R. J. Patton, Non-linear dynamic systems fault detection and isolation using fuzzy observers, Proc. of Instn. Mech. Engrs. Part I: Journal of Systems and Control Engineering, vol.213, no.6, pp.467-476, 1999.
25. H. N. Wu and H. Y. Zhang, Reliable H1 fuzzy control for continuous-time nonlinear systems with actuator failures, IEEE Transactions on Fuzzy Systems, vol.14, no.5, pp.609-618, 2006.
26. F. Delmotte, T. M. Guerra and M. Ksantini, Continuous Takagi-Sugeno's models: Reduction of the number of LMI conditions in various fuzzy control design technics, IEEE Transactions on Fuzzy Systems, vol.15, no.3, pp.426-438, 2007.
27. G. Schwarz, Estimating the dimension of a model, Annals of Statistics, vol.6, no.2, pp.461-464, 1978.