IEEE Transactions on Fuzzy Systems
Papers 3034
1 page of 304 pages (3,034 results)
#1Meftahul Ferdaus (UNSW: University of New South Wales)H-Index: 7
#2Mahardhika Pratama (NTU: Nanyang Technological University)H-Index: 17
Last.Matthew A. Garratt (UNSW: University of New South Wales)H-Index: 16
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Data stream has been the underlying challenge in the age of big data because it calls for real-time data processing with the absence of a retraining process and/or an iterative learning approach. In the realm of the fuzzy system community, data stream is handled by algorithmic development of self-adaptive neuro-fuzzy systems (SANFS) characterized by the single-pass learning mode and the open structure property that enables effective handling of fast and rapidly changing natures of data streams. ...
8 CitationsSource
#1Hangyao Wu (Sichuan University)H-Index: 1
#2Peijia Ren (Sichuan University)H-Index: 8
Last.Zeshui Xu (Sichuan University)H-Index: 88
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Aiming at validly improving the efficiency and quality of hospital expert consultation, a consensus model under uncertainty is established to operate a hospital decision support system (HDSS). Considering that expert consultation is commonly used in emergency events associated with life rescue where uncertainty and complexity exist, hesitant fuzzy linguistic terms are adopted. Additionally, since pairwise comparison information is efficient to express individual judgment, a novel concept of sati...
1 CitationsSource
#1Zhang Huaguang (NU: Northeastern University)H-Index: 64
#2Hanguang Su (NU: Northeastern University)H-Index: 3
Last.Yanhong Luo (NU: Northeastern University)H-Index: 17
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In this paper, by incorporating the event-triggered mechanism and the adaptive dynamic programming algorithm, a novel near-optimal control scheme for a class of unknown nonlinear continuous-time non-zero-sum (NZS) differential games is investigated. First, a generalized fuzzy hyperbolic model based identifier is established, using only the input–output data, to relax the requirement for the complete system dynamics. Then, under the event-based framework, the coupled Hamilton–Jacobi equations are...
4 CitationsSource
#1Nallappan Gunasekaran (Kunsan National University)H-Index: 5
#2Young Hoon Joo (Kunsan National University)H-Index: 12
In this paper, sampled-data control is proposed to stabilize the nonlinear system, which is expressed as a Takagi–Sugeno (T–S) fuzzy submodels. Based on suitable Lyapunov– Krasovskii functional (LKF) along with new weighted integral inequalities, the sufficient conditions are derived in terms of linear matrix inequalities, which ensure the exponential stability of the proposed closed loop T–S fuzzy system. The peculiarity of this paper is: as novel integral inequalities and LKF are proposed, les...
#1Yi Wen Kerk (Deakin University)H-Index: 1
#2Kai Meng Tay (UNIMAS: Universiti Malaysia Sarawak)H-Index: 14
Last.Chee Peng Lim (Deakin University)H-Index: 33
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In this paper, we introduce the notion of a monotone fuzzy partition , which is useful for constructing a monotone zero-order Takagi–Sugeno–Kang Fuzzy Inference System (ZOTSK-FIS). It is known that a monotone ZOTSK-FIS model can always be produced when a consistent, complete, and monotone fuzzy rule base is used. However, such an ideal situation is not always available in practice, because a fuzzy rule base is susceptible to uncertainties, e.g., inconsistency, incompleteness, and nonmonotonicity...
#1Jianbin Qiu (HIT: Harbin Institute of Technology)H-Index: 52
#2Kangkang Sun (HIT: Harbin Institute of Technology)H-Index: 2
Last.Huijun Gao (HIT: Harbin Institute of Technology)H-Index: 105
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This paper studies the problem of fuzzy adaptive event-triggered control for a class of pure-feedback nonlinear systems, which contain unknown smooth functions and unmeasured states. Fuzzy logic systems are adopted to approximate unknown smooth functions and a fuzzy state observer is designed to estimate unmeasured states. Via the event-triggered control technique, the control signal of the fixed threshold strategy is obtained. By converting the tracking error into a new virtual error variable, ...
58 CitationsSource
#1Wei Wang (Liaoning University of Technology)
#2Shaoceng Tong (Liaoning University of Technology)H-Index: 68
The adaptive fuzzy containment control problem is addressed for multiple uncertain nonlinear strict-feedback systems with immeasurable states and multiple leaders under directed communication graphs. By utilizing fuzzy logic systems to model the followers’ dynamics, a distributed fuzzy state observer is designed for the state estimation using only the relative position information. Then, an observer-based containment control scheme is constructed by the adaptive fuzzy control technique as well a...
#1Xiaomiao Li (QMUL: Queen Mary University of London)H-Index: 3
#2Kamyar Mehran (QMUL: Queen Mary University of London)H-Index: 5
This paper proposes a novel Lyapunov stabilization analysis of discrete-time polynomial-fuzzy-model-based control systems with time delay under positivity constraint. The polynomial fuzzy model is constructed to describe the dynamics of a nonlinear discrete-time system with time delay. A model-based polynomial fuzzy controller is designed using nonparallel distributed compensation technique to stabilize the system while driving the system states to positive using the positivity constraints. The ...
This paper proposes a hybrid fuzzy dynamic surface control (DSC) method combined with a supertwisting control (STC) method and a supertwisting nonlinear disturbance observer (STO) for multi-input multi-output nonlinear strict-feedback systems is proposed, in addition to a new partial tracking error constraining method. For the design of the stabilizing controls of the DSC, the virtual tracking errors in recursive procedures were transformed into the design variables of the STC. The uncertainties...
#1Salim Rezvani (SZU: Shenzhen University)H-Index: 1
#2Xi-Zhao Wang (SZU: Shenzhen University)H-Index: 39
Last.Farhad Pourpanah (SZU: Shenzhen University)H-Index: 3
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Fuzzy twin support vector machine (FTSVM) is an effective machine learning technique that is able to overcome the negative impact of noise and outliers in tackling data classification problems. In the FTSVM, the degree of membership function in the sample space describes the space between input data and class center, while ignoring the position of input data in the feature space and simply miscalculated the ledge support vectors as noises. This paper presents an intuitionistic FTSVM (IFTSVM) tha...
2 CitationsSource
Top fields of study
Machine learning
Fuzzy control system
Fuzzy logic
Control theory