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International Journal of Applied Mathematics and Computer Science

Journal of University of Zielona Gora and Lubuskie Scientific Society

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Volume 22, Issue 1

Issues

Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model

Dezhi Xu
  • College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Bin Jiang
  • College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Peng Shi
  • Department of Computing and Mathematical Sciences, University of Glamorgan, Pontypridd CF37 1DL, UK
  • School of Engineering and Science, Victoria University, Melbourne, Vic 8001, Australia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2012-03-22 | DOI: https://doi.org/10.2478/v10006-012-0014-9

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.

Keywords: actuator fault estimation; Takagi-Sugeno fuzzy models; robust sliding mode observer; inverse system method

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About the article


Published Online: 2012-03-22

Published in Print: 2012-03-01


Citation Information: International Journal of Applied Mathematics and Computer Science, Volume 22, Issue 1, Pages 183–196, ISSN (Print) 1641-876X, DOI: https://doi.org/10.2478/v10006-012-0014-9.

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