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Keywords = membership-function-dependent H∞/H_ performance

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21 pages, 821 KB  
Article
Fuzzy Fault Detection Observer Design for Unmanned Marine Vehicles Based on Membership-Function-Dependent H/H_ Performance
by Yue Wu, Yang Wang, Kai Zhang, Shanfeng Zhang and Ying Wu
J. Mar. Sci. Eng. 2024, 12(8), 1288; https://doi.org/10.3390/jmse12081288 - 31 Jul 2024
Viewed by 1025
Abstract
This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, [...] Read more.
This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, a new H/H_ performance index, which depends on the membership functions, is defined. Then, based on the membership-function-dependent H/H_ performance index, a new fuzzy FD observer strategy, where the fuzzy submodels are not all required to be with the same H_ performance index, is developed to detect the sensor fault in UMVs; the corresponding synthesis conditions of the FD observer are derived based on the Lyapunov theory. Different from the conventional FD strategies, in the proposed membership-function-dependent FD method, the fuzzy submodels—which the system always works on—can have a larger H_ performance index, such that the performance of the FD can be improved. In the end, an example is given to show the effectiveness of the presented method. Full article
(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)
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21 pages, 1741 KB  
Article
The Stabilization of a Nonlinear Permanent-Magnet- Synchronous-Generator-Based Wind Energy Conversion System via Coupling-Memory-Sampled Data Control with a Membership-Function-Dependent H Approach
by Anto Anbarasu Yesudhas, Seong Ryong Lee, Jae Hoon Jeong, Narayanan Govindasami and Young Hoon Joo
Energies 2024, 17(15), 3746; https://doi.org/10.3390/en17153746 - 29 Jul 2024
Cited by 2 | Viewed by 1267
Abstract
This study presents the coupling-memory-sampled data control (CMSDC) design for the Takagi–Sugeno (T-S) fuzzy system that solves the stabilization issue of a surface-mounted permanent-magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). A fuzzy CMSDC scheme that includes the sampled data control (SDC) [...] Read more.
This study presents the coupling-memory-sampled data control (CMSDC) design for the Takagi–Sugeno (T-S) fuzzy system that solves the stabilization issue of a surface-mounted permanent-magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). A fuzzy CMSDC scheme that includes the sampled data control (SDC) and memory-sampled data control (MSDC) is designed by employing a Bernoulli distribution order. Meanwhile, the membership-function-dependent (MFD) H performance index is presented, mitigating the continuous-time fuzzy system’s disturbances. Then, by using the Lyapunov–Krasovskii functional with the MFD H performance index, the data of the sampling pattern, and a constant signal transmission delay, sufficient conditions are derived. These sufficient conditions are linear matrix inequalities (LMIs), ensuring the global asymptotic stability of a PMSG-based WECS under the designed control technique. The proposed method is demonstrated by a numerical simulation implemented on the PMSG-based WECS. Finally, Rossler’s system demonstrates the effectiveness and superiority of the proposed method. Full article
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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