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Enhancing MPPT performance of a grid-connected Doubly-Fed induction generator-based wind power plant using hybrid ANFIS-PI control strategy. [PDF]
Sci RepBiyazne LW +3 more
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A sensor-fault resilient artificial pancreas using type-3 fuzzy logic and predictive controls. [PDF]
Sci RepMai VT +3 more
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Artificial neural network modeling and optimization of an electrochemical biosensor for plasma miR-155-based breast cancer detection. [PDF]
Sci RepImani A +3 more
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T-S fuzzy approach for real-time vehicle state estimation and road safety enhancement. [PDF]
Sci RepSaber M +4 more
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Sugeno's fuzzy measure and fuzzy clustering
Fuzzy Sets and Systems, 1985Proposed is an iterative clustering method making use of Sugeno's fuzzy measure. The minimized performance index is of the form \(\sum^{c}_{i=1}\sum^{n}_{j=1}g_{ij}d_{ij}\), where c and n stand for the number of clusters (classes) and objects clustered, respectively.
Leszczyński, K. +2 more
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Observers for Takagi-Sugeno fuzzy systems
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2002We focus on the analysis and design of two different sliding mode observers for dynamic Takagi-Sugeno (TS) fuzzy systems. A nonlinear system of this class is composed of multiple affine local linear models that are smoothly interpolated by weighting functions resulting from a fuzzy partitioning of the state space of a given nonlinear system subject to ...
P, Bergsten, R, Palm, D, Driankov
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Takagi-Sugeno Type Fuzzy Automaton Model
International Conference on Fuzzy Systems, 2009Tracking the status of an event-driven, large control system is a difficult problem. Those systems often encounter unexpected events in an uncertain environment. Using a fuzzy automaton offers an effective approximation method to model continuous and discrete signals in a single theoretical framework.
Janos L. Grantner, George A. Fodor
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Multilabel Takagi-Sugeno-Kang Fuzzy System
IEEE Transactions on Fuzzy Systems, 2022Multi-label classification can effectively identify the relevant labels of an instance from a given set of labels. However, the modeling of the relationship between the features and the labels is critical to the classification performance. To this end, we pro-pose a new multi-label classification method, called Multi-Label Takagi-Sugeno-Kang Fuzzy ...
Qiongdan Lou +4 more
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Flexible takagi-sugeno fuzzy systems
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., 2006In the paper, a new class of Takagi-Sugeno fuzzy systems is derived. Various parameters and weights are incorporated into construction of such systems. The approach presented in the paper introduces more flexibility to the structure and design of neuro-fuzzy systems.
K. Cpalka, L. Rutkowski
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Control laws for Takagi–Sugeno fuzzy models
Fuzzy Sets and Systems, 2001Abstract This work presents control laws for fuzzy models of Takagi–Sugeno (TS) (Sugeno and Kang, Fuzzy Sets and Systems 28 (1988) 15–33, Takagi and Sugeno, IEEE Trans. Systems Man Cybernet. 15(1) (1985) 116–132). These laws are not directly put in the classical form called PDC for parallel distributed compensation (Wang et al., IEEE Trans.
Guerra, Thierry Marie +1 more
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