We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Robust fault detection for Takagi-Sugeno discrete models: Application for a three-tank system

by H. Ghorbel, M. Souissi, M. Chaabane, F. Tadeo
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 18
Year of Publication: 2012
Authors: H. Ghorbel, M. Souissi, M. Chaabane, F. Tadeo
10.5120/6360-6599

H. Ghorbel, M. Souissi, M. Chaabane, F. Tadeo . Robust fault detection for Takagi-Sugeno discrete models: Application for a three-tank system. International Journal of Computer Applications. 44, 18 ( April 2012), 1-7. DOI=10.5120/6360-6599

@article{ 10.5120/6360-6599,
author = { H. Ghorbel, M. Souissi, M. Chaabane, F. Tadeo },
title = { Robust fault detection for Takagi-Sugeno discrete models: Application for a three-tank system },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 18 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number18/6360-6599/ },
doi = { 10.5120/6360-6599 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:35:50.685015+05:30
%A H. Ghorbel
%A M. Souissi
%A M. Chaabane
%A F. Tadeo
%T Robust fault detection for Takagi-Sugeno discrete models: Application for a three-tank system
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 18
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we present a fuzzy observer based on Takagi- Sugeno (TS) models, to estimate simultaneously the system state and the sensors faults of discrete time nonlinear systems. The method uses the technique of descriptor systems, by considering the sensor faults as auxiliary states variables. More precisely, This paper addresses the problem of index fault detection observer to ensure the sensitivity against the faults. The proposed method is based on the use of the Lyapunov theory to ensure the stability of the system. Necessary and sufficient conditions are obtained in terms of Linear Matrix Inequalities (LMIs), in order to determine the observer gains. An application of the fault estimation method on an hydraulic process with three tanks, using TS models is realized. Simulation and experimental results show the effectiveness of the proposed method.

References
  1. Khedher, A. , Benothman, K. , Maquin, D. and Benrejeb, M. , "An approach of faults estimation in Takagi-Sugeno fuzzy systems". 8th ACS/IEEE International Conference on Computer Systems and Applications, AICCS 2010, Hammamet, Tunisia, May 2010.
  2. Marx, D. , Koenig, B. and Ragot, J. , "Design of observers for Takagi- Sugeno descriptor systems with unknown inputs and application to fault diagnosis". IET Control Theory and Applications, vol. 1, no. 5, pp. 1487–1495, 2007.
  3. Castillo-Toledo, B. , and Anzurez-Marin, J. , "Model-based fault diagnosis using sliding mode observers to Takagi-Sugeno fuzzy model". IEEE Congress on Intelligent Control, Limassol, Cyprus, 2005.
  4. Ichalal, D. , Marx, D. B. , Ragot, J. and Maquin, D. , "Observer based actuator fault tolerant control for nonlinear Takagi-Sugeno systems: an LMI approach". 18th Mediterranean Conference on Control and Automation, MED'10, Athens, Greece, June 23-25, 2010.
  5. Wang, H. , Wang, J. , Liu, J. and Lam, J. , "Iterative LMI approach for robust fault detection observer design". In Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, Hawaii, USA, December 2003.
  6. Ghorbel, H. , Ghamgui, M. , Souissi, M. and Chaabane, M. , "Modelling and robust control for Three Tanks System using fuzzy approach". Conference JTEA. 27 March 2010.
  7. Jaimoukha, I. , and Li, Z. "A matrix factorization solution to the H?/H? fault detection problem," Automatica, vol. 42, no. 11, pp. 1907–1912, November 2006.
  8. Liu, J. , Wang, J. L and Yang, G. "An LMI approach to minimum sensitivity analysis with application to fault detection," Automatica, vol. 41, no. 11, pp. 1995–2004, 2005.
  9. Guoa, J. , Huanga, X. and Cui, Y. "Design and analysis of robust fault detection filter using LMI tools". Computers and Mathematics with Applications, 57(11-12):1743–1747, June 2009.
  10. Chadli, M. , Akhenak, A. , Ragot, J. and Maquin, D. , "On the design of observer for unknown inputs fuzzy models". International Journal of Automation and Control, 2(1):113–125, 2008.
  11. Blanke, M. , Kinnaert, M. , Lunze, J. and Staroswiecki, M. , " Diagnosis and FTC". Springer-Verlag, London, 2006.
  12. Bouattour, M. , Chadli, M. , El. Hajjaji, A. and Chaabane, M. , "State and faults estimation for T-S models and application to fault diagnosis". 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS'09, Barcelona, July 30 2009.
  13. Bouattour, M. , Chadli, M. , El. Hajjaji, A. and Chaabane, M. , "H? sensor faults estimation for T-S models using descriptor techniques: Application to fault diagnosis". In IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, 20-24 August 2009, pp. 251–255.
  14. Chadli, M. , Akhenak, A. , Ragot, J. and Maquin, D. , "State and unknown input estimation for discrete time multiple model". Journal of the Franklin Institute, vol. 346, no. 6, pp. 593–610, 2009.
  15. Zhong, M. , Ding, S. , Lam, J. and Wang, H. , "An LMI approach to design robust fault detection filter for uncertain LTI systems," Automatica, vol. 39, pp. 543–550, 2003.
  16. Patton, R. , Frank, P. M. and Clark, R. , "Issues of fault diagnosis for dynamic systems". Springer-Verlag, London, 1999.
  17. Patton, R. and Chen, J. , "Obeserver based fault detection and isolation : robustness and applications". Control Eng. Practice, vol. 5, no. 5, pp. 671–682, 1997.
  18. Orjuela, R. , Marx, D. B. , Ragot, J. and Maquin, D. , "Diagnostic des systèmes non linéaires par une approche multimodèle". 6th Conférence Internationale Francophone d'Automatique, CIFA 2010, Nancy, France, June 2-4, 2010.
  19. Patton, R. , and Chen, J. , "Fuzzy Observers for Non-linear Dynamic Systems Fault Diagnosis". IEEE Conference on Decision asd Control Tampa, Florida USA, 1998.
  20. Nguang, S. , Shi, P. and Ding, S. , "Fault detection for uncertain fuzzy systems: an LMI approach". IEEE Tr. Fuzzy Systems, vol. 15, no. 6, pp. 1251–1262, 2007.
  21. Takagi, T. , and Sugeno, M. , "Fuzzy identification of systems and its applications to modeling and control". IEEE Trans. Syst. , Man, Cybern. , vol. SMC-15, no. 4, pp. 116–132, Aug. 1985.
  22. Taniguchi, T. , Tanaka, K. and Wang, H. O. , "Fuzzy descriptor systems and nonlinear model following control". IEEE Trans. Fuzzy Syst. , vol. 8, no. 4, pp. 442–452, Aug. 2000.
  23. Bouarar, T. , Guelton, K. , Mansouri, B. and Manamanni, N. , "LMI Stability Conditions for Takagi-Sugeno Uncertain Descriptors". International Conference on Fuzzy Systems (FUZZ-IEEE). London, UK, July 2007.
  24. Gao, Z. , and D. W. C. , Ho. , "State/Noise Estimator for Descriptor Systems with Application to Sensor Fault Diagnosis". IEEE Transactions on Signal Processing, vol. 54, no. 4, 2006.
  25. Gao, Z. , Shi, X. and Ding, S. X. , "Fuzzy state-disturbance observer design for T-S fuzzy systems with application to sensor fault estimation". IEEE Transactions on SMC-part B, vol. 38, no. 3: 875 - 880, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Non Linear System Ts Fuzzy Model Descriptor Observer Sensor Fault Estimation Lmi Tanks System

Powered by PhDFocusTM