Fault estimation Observer Design for Discrete-Time Takagi-Sugeno Fuzzy Systems Based on Piecewise Lyapunov Functions

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Zhang, Ke, Jiang, Bin and Shi, Peng (2012) Fault estimation Observer Design for Discrete-Time Takagi-Sugeno Fuzzy Systems Based on Piecewise Lyapunov Functions. IEEE Transactions on Fuzzy Systems, 20 (1). pp. 192-200. ISSN 1063-6706

Abstract

This paper studies the problem of robust fault estimation (FE) observer design for discrete-time Takagi–Sugeno (T–S) fuzzy systems via piecewise Lyapunov functions. Both the full-order FE observer (FFEO) and the reduced-order FE observer (RFEO) are presented. The objective of this paper is to establish a novel framework of the FE observer with less conservatism. First, under the multiconstrained design, an FFEO is proposed to achieve FE for discrete-time T–S fuzzy models. Then, using a specific coordinate transformation, an RFEO is constructed, which results in a new fault estimator to realize FE using current output information. Furthermore, by the piecewise Lyapunov function approach, less conservative results on both FFEO and RFEO are derived by introducing slack variables. Simulation results are presented to illustrate the advantages of the theoretic results that are obtained in this paper.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/10453
DOI https://doi.org/10.1109/TFUZZ.2011.2168961
Official URL http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn...
Subjects Current > FOR Classification > 0801 Artificial Intelligence and Image Processing
Current > FOR Classification > 0802 Computation Theory and Mathematics
Historical > SEO Classification > 970108 Expanding Knowledge in the Information and Computing Sciences
Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Historical > Faculty/School/Research Centre/Department > School of Engineering and Science
Keywords ResPubID25087, discrete-time system, fault estimation, FE, piecewise Lyapunov functions, Takagi–Sugeno fuzzy model, T-S fuzzy model, fuzzy system
Citations in Scopus 168 - View on Scopus
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