Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 29, Issue 9, Pages 2760-2773Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2020.3006987
Keywords
Fault detection; finite frequency performances; interval type-2 T-S fuzzy systems; membership function dependent
Funding
- Research Grants Council of the Hong Kong Special Administrative Region of China [CityU-11211818]
- National Natural Science Foundation of China [61873311]
- Hong Kong, Macao, and Taiwan Science and Technology Cooperation Program of Shanghai [19510760200]
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This article investigates the problem of finite frequency fault detection filtering design for uncertain nonlinear systems based on interval type-2 Takagi-Sugeno fuzzy models. A novel approach for finite frequency filtering synthesis is proposed, and two algorithms with linear matrix inequality constraints are developed to optimize system performance. Simulation studies demonstrate the effectiveness of the proposed method.
This article studies the problem of finite frequency fault detection filtering design for uncertain nonlinear systems based on interval type-2 Takagi-Sugeno fuzzy models. It is assumed that the frequencies of disturbances and faults are in finite frequency sets, respectively. The objective is to design an admissible filter such that the fault detection system is asymptotically stable with prescribed finite frequency H-infinity and H- performances. Based on Fourier transform and Projection lemma, finite frequency filtering synthesis results are obtained. Then, a novel membership-function-dependent finite frequency fault detection filtering design approach is proposed by using the information of the lower and upper membership functions together with the footprint of uncertainties. Two algorithms with linear matrix inequality constraints are developed to optimize the finite frequency H-infinity performance and the finite frequency H- performance, respectively. Finally, simulation studies are provided to show the effectiveness of the proposed method.
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