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International Journal of Applied Mathematics and Computer Science
Journal of University of Zielona Gora and Lubuskie Scientific Society
IMPACT FACTOR 2015: 1.037
5-year IMPACT FACTOR: 1.151
Rank 83 out of 254 in category Applied Mathematics in the 2015 Thomson Reuters Journal Citation Report/Science Edition
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Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China1
Department of Computing and Mathematical Sciences, University of Glamorgan, Pontypridd CF37 1DL, UK2
School of Engineering and Science, Victoria University, Melbourne, Vic 8001, Australia3
This content is open access.
Citation Information: International Journal of Applied Mathematics and Computer Science. Volume 22, Issue 1, Pages 183–196, ISSN (Print) 1641-876X, DOI: 10.2478/v10006-012-0014-9, March 2012
- Published Online:
Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model
Based on a Takagi-Sugeno (T-S) fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T-S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T-S fuzzy model, and an inverse system method is used to estimate the actuator fault. Next, the second fault estimation strategy is developed. Compared with some existing techniques, such as adaptive and sliding mode methods, the one presented in this paper is easier to be implemented in practice. Finally, two numerical examples are given to demonstrate the efficiency of the proposed techniques.
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