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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 951953, 25 pages
A Reduced-Order TS Fuzzy Observer Scheme with Application to Actuator Faults Reconstruction
Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 042 00 Košice, Slovakia
Received 11 October 2012; Accepted 23 November 2012
Academic Editor: Peng Shi
Copyright © 2012 Dušan Krokavec and Anna Filasová. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- J. Chen and R. J. Patton, Robust Model-Based Fault Diagnosis for Dynamic Systems, Kluwer Academic Publishers, Norwell, Mass, USA, 1999.
- S. Ding, Model-Based Fault Diagnosis Techniques. Design Schemes, Algorithms, and Tools, Springer, Berlin, Germany, 2008.
- W. Chen and M. Saif, “Observer-based strategies for actuator fault detection, isolation and estimation for certain class of uncertain nonlinear systems,” IET Control Theory and Applications, vol. 1, no. 6, pp. 1672–1680, 2007.
- W. Chen, A. Q. Khan, M. Abid, and S. X. Ding, “Integrated design of observer based fault detection for a class of uncertain nonlinear systems,” International Journal of Applied Mathematics and Computer Science, vol. 21, no. 3, pp. 423–430, 2011.
- A. Zolghadri, D. Henry, and M. Monsion, “Design of nonlinear observers for fault diagnosis: a case study,” Control Engineering Practice, vol. 4, no. 11, pp. 1535–1544, 1996.
- F. E. Thau, “Observing the state of nonlinear dynamical systems,” International Journal of Control, vol. 17, no. 3, pp. 471–479, 1973.
- A. J. Koshkouei and A. S. I. Zinober, “Partial Lipschitz nonlinear sliding mode observers,” in Proceedings of the 7th Mediterranean Conference on Control and Automation (MED '99), pp. 2350–2359, Haifa, Israel, 1999.
- F. Zhu and F. Cen, “Full-order observer-based actuator fault detection and reduced-order observer-based fault reconstruction for a class of uncertain nonlinear systems,” Journal of Process Control, vol. 20, no. 10, pp. 1141–1149, 2010.
- X.-G. Yan and C. Edwards, “Nonlinear robust fault reconstruction and estimation using a sliding mode observer,” Automatica, vol. 43, no. 9, pp. 1605–1614, 2007.
- J. Yu, G. Sun, and H. R. Karimi, “Fault-reconstruction-based cascaded sliding mode observers for descriptor linear systems,” Mathematical Problems in Engineering, vol. 2012, Article ID 623426, 20 pages, 2012.
- F. Zhu, “State estimation and unknown input reconstruction via both reduced-order and high-order sliding mode observers,” Journal of Process Control, vol. 22, no. 1, pp. 296–302, 2012.
- H. Wang and S. Daley, “Actuator fault diagnosis: an adaptive observer-based technique,” IEEE Transactions on Automatic Control, vol. 41, no. 7, pp. 1073–1078, 1996.
- X. Zhang, M. M. Polycarpou, and T. Parisini, “Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation,” Automatica, vol. 46, no. 2, pp. 290–299, 2010.
- W. Zhang, H. Su, H. Wang, and Z. Han, “Full-order and reduced-order observers for one-sided Lipschitz nonlinear systems using Riccati equations,” Communications in Nonlinear Science and Numerical Simulation, vol. 17, no. 12, pp. 4968–4977, 2012.
- T. Takagi and M. Sugeno, “Fuzzy identification of systems and its applications to modeling and control,” IEEE Transactions on Systems, Man and Cybernetics, vol. 15, no. 1, pp. 116–132, 1985.
- L. Wu, X. Su, P. Shi, and J. Qiu, “Model approximation for discrete-time state-delay systems in the TS fuzzy framework,” IEEE Transactions on Fuzzy Systems, vol. 19, no. 2, pp. 366–378, 2011.
- Z. Gao, B. Jiang, P. Shi, and Y. Xu, “Fault accommodation for near space vehicle attitude dynamics via T-S fuzzy models,” International Journal of Innovative Computing, Information and Control, vol. 6, no. 11, pp. 4843–4856, 2010.
- Z. Lendek, T. M. Guerra, R. Babuška, and B. De Schutter, Stability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy Models, Springer, Berlin, Germany, 2010.
- K. M. Passino and S. Yurkovich, Fuzzy Control, Addison-Wesley Longman, Berkeley, Calif, USA, 1998.
- K. Tanaka and H. O. Wang, Fuzzy Control Systems Design and Analysis. A Linear Matrix Inequality Approach, John Wiley & Sons, New York, NY, USA, 2001.
- M. Chadli, “An LMI approach to design observer for unknown inputs Takagi-Sugeno fuzzy models,” Asian Journal of Control, vol. 12, no. 4, pp. 524–530, 2010.
- D. Ichalal, B. Marx, J. Ragot, and D. Maquin, “Design of observers for Takagi-Sugeno discrete-time systems with unmeasurable premise variables,” in Proceedings of the 5th Workshop on Advanced Control and Diagnosis (ACD '07), Grenoble, France, 2007.
- A. M. Nagy Kiss, B. Marx, G. Mourot, G. Schutz, and J. Ragot, “Observers design for uncertain Takagi-Sugeno systems with unmeasurable premise variables and unknown inputs. Application to a wastewater treatment plant,” Journal of Process Control, vol. 21, no. 7, pp. 1105–1114, 2011.
- D. Zhang, H. Wang, B. Lu, and Z. Wang, “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, vol. 8, no. 1B, pp. 633–645, 2012.
- K. Zhang, B. Jiang, and P. Shi, Observer-Based Fault Estimation and Accomodation for Dynamic Systems, Springer, Berlin, Germany, 2012.
- 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 B, vol. 38, no. 3, pp. 875–880, 2008.
- D. Xu, B. Jiang, and P. Shi, “Nonlinear actuator fault estimation observer: an inverse system approach via a T-S fuzzy model,” International Journal of Applied Mathematics and Computer Science, vol. 22, no. 1, pp. 183–196, 2012.
- D. Krokavec and A. Filasová, “An approach to reconstruction of actuator faults for a class of nonlinear systems,” in Proceedings of the 8th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes (SAFEPROCESS ”12), pp. 216–221, Mexico City, Mexico, 2012.
- D. Krokavec and A. Filasová, “Reducer-order fuzzy-observer-based actuator fault reconstruction for a class of nonlinear systems,” in Proceedings of the 6th IASTED International Conference on Computational Intelligence and Bioinformatics (CIB '11), pp. 61–68, Pittsburgh, Pa, USA, 2011.
- D. Krokavec and A. Filasová, Dynamic Systems Diagnosis, Elfa, Kosice, Slovakia, 2007.
- Q.-G. Wang, Decoupling Control, vol. 285 of Lecture Notes in Control and Information Sciences, Springer, Berlin, Germany, 2003.
- P. Gerland, D. Groß, H. Schulte, and A. Kroll, “Robust adaptive fault detection using global state information and application to mobile working machines,” in Proceedings of the 1st Conference on Control and Fault-Tolerant Systems (SysTol '10), pp. 813–818, Nice, France, October 2010.
- D. Peaucelle, D. Henrion, Y. Labit, and K. Taitz, User's Guide for SeDuMi Interface 1.04, LAAS-CNRS, Toulouse, France, 2002.
- D. Krokavec and A. Filasová, “Optimal fuzzy control for a class of nonlinear systems,” Mathematical Problems in Engineering, vol. 2012, Article ID 481942, 29 pages, 2012.