Ever since the first hybrid fuzzy rough set model was proposed in the early 1990’s, many researchers have focused on the definition of the lower and upper approximation of a fuzzy set by means of a fuzzy relation. In this paper, we review those proposals which generalize the logical connectives and quantifiers present in the rough set approximations by means of corresponding fuzzy logic operati...

The paper presents a novel type of fuzzy sets, called time-Varying Fuzzy Sets (VFS). These fuzzy sets are based on the Gaussian membership functions, they are depended on the error and they are characterized by the displacement of the kernels to both right and left side of the universe of discourse, the two extremes kernels of the universe are fixed for all time. In this work we focus only on t...

This paper presents a new mathematical model for a bi-objective job shop scheduling problem with sequence-dependent setup times that minimizes the weighted mean completion time and the weighted mean tardiness time. For solving this multi-objective model, we develop a fuzzy multi-objective linear programming (FMOLP) model. In this problem, a proposed FMOLP method is applied with respect to the o...

Abstract: In this paper,we propose a low effort control scheme for chaotic systems by using fuzzy model-based design method. First, we represent nonlinear systems into T-S fuzzy models in a working region covering the point to be regulated. The stability condition of the overall system is formulated into (LMIs). To guarantee the stability, the region of attraction is also investigated. Accordin...

In this paper a fuzzy tracking control is proposed for non linear dynamic system with bounded external disturbances and admissible uncertainties described as TakagiSugeno (T-S) fuzzy model. Using a tracking reference model, a stability condition scheme based on an augmented system with a guaranteed H∞ performance is proposed to obtain tracking performances. The main result of this paper is to p...

In this dissertation Euler-Lagrange’s method is used to model the dynamics of two linked rigid manipulator. The multi input and the multi output model is found to be nonlinear. To observe and control the output response of manipulator, SIMULINK model is designed using S-Function block without any controller and the response found is unbounded. In order to control the position of the manipulator...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

In this paper, a novel fault-tolerant control scheme is proposed for a class of uncertain multiple-input-multiple-output (MIMO) nonlinear systems based on online fuzzy clustering and identification. The unknown nonlinear function of the system is identified online using an evolving Takagi-Sugeno (T-S) fuzzy model and the fault-tolerant control law is designed based on the identified fuzzy model...

Takagi–Sugeno (T-S) fuzzy models are now often used to describe complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear submodels. In this note, the T-S fuzzy model approach is exploited to establish stability criteria for a class of nonlinear stochastic systems with time delay. Sufficient conditions are derived in the format of linear matrix inequalities...

nowadays we know effective supply chain management a key to business success. therefore, supply chain managers use many practices for scm effectiveness and many tools as their enablers. nevertheless, literature about causal relations between sc enablers and scm practices and performance is scarce. this study reports a cognitive mapping of causal relationships between scm practices, sc enablers ...