and Applied Analysis 3 x ν αx, t ν x, t/|α| for each α/ 0, xi ν x, t ν y, s ≥ ν x y, t s , xii ν x, · : 0,∞ → 0, 1 is continuous, xiii limt→∞ν x, t 0 and limt→ 0ν x, t 1. In this case μ, ν is called an intuitionistic fuzzy norm. Example 1.4 cf. 37 . Let X, ‖·‖ be a normed space, a∗b ab, and a b min a b, 1 for all a, b ∈ 0, 1 . For all x ∈ X and every t > 0 and k 1, 2, consider μk x, t ⎧ ⎨ ⎩ t t...

In this paper, first we give the definitions of various indicators of fuzzy relations and their basic properties. Then we investigate the relationships between these indicators, particularly between those of T-transitivity, negative S-transitivity, T–S-semitransitivity and T–S-Ferrers property. The investigation is divided into three parts: results in the general case, results under a condition...

K e y w o r d s C o m p e n s a t o r y , Fuzzy similarity measure, Inverted wedge system, Backpropagation algorithm. 1. I N T R O D U C T I O N Recently, the neural fuzzy approach to system modeling has become a popular research topic [110]. Moreover, the neural fuzzy method possesses the advantages of both the pure neural and the fuzzy methods; it brings the low-level learning and computation...

A novel optimal method is developed to improve the identification and estimation of Takagi-Sugeno (TS) fuzzy model. The idea comes from the fact that the main drawback of T-S model is that it can not be applied when the membership functions are overlapped by pairs. This limits the application of the T-S model because this type of membership function has been widely used in the stability and con...

This paper presents a gain-scheduling output feedback control design method for T-S fuzzy systems with actuator saturation. Different from existing control design methods for T-S fuzzy systems, the basic idea of the proposed approach is to transform the T-S fuzzy model with saturation nonlinearity into the form of linear fractional transformation (LFT). Instead of commonly used fuzzy controller...

This research frame work investigates the application of a clustered based Neuro-fuzzy system to nonlinear dynamic system modeling from a set of input-output training patterns. It is concentrated on the modeling via Takagi-Sugeno (T-S) modeling technique and the employment of fuzzy clustering to generate suitable initial membership functions. Hence, such created initial memberships are then emp...

The problem of robust fuzzy control for a class of nonlinear fuzzy impulsive singular perturbed systems with time-varying delay is investigated by employing Lyapunov functions. The nonlinear delay system is built based on the well-known T–S fuzzy model. The so-called parallel distributed compensation idea is employed to design the state feedback controller. Sufficient conditions for global expo...

In this paper we consider the control problem of Dynamic Positioning Systems for Ships (DPSS). It interests as a case which study in nonlinear controller design because the model exhibits nonlinear interaction in three degrees of freedom (surge, sway, and yaw) by means of main propellers aft of the ship. The DPSS system considered in this paper is modeled by a Takagi-Sugeno (T-S) type fuzzy mod...

We consider the problem of passivity control for a kind of T-S fuzzy system in the literature [1].We will extend it to the uncertain T-S fuzzy descriptor systems with time-delay in this paper. Generally speaking, a mathematical model cannot be used to exactly describe a dynamical system in practice because it is inevitable to include some degrees of uncertainties in the systems. Moreover, time-...

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of...