This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...

The paper presents aspects concerning the tuning of two-degree-of-freedom (2-DOF) fuzzy controllers focused on 2-DOF PI-fuzzy controllers and 2-DOF PIDfuzzy controllers. 2-DOF Mamdani and Takagi-Sugeno fuzzy control system structures are offered. The tuning is based on mapping the parameters of the linear PI and PID controllers to the parameters of the fuzzy controllers in terms of the modal eq...

Multivariable liquid level control is essential in process industries to ensure quality of the product and safety of the equipment. However, the significant problems of the control system include excessive time consumption and percentage overshoot, which result from ineffective performance of the tuning methods of the PID controllers used for the system. In this paper, fuzzy logic was used to t...

a‎s we know, developing mathematical models and numerical procedures that would appropriately treat and solve systems of linear equations where some of the system's parameters are proposed as fuzzy numbers is very important in fuzzy set theory. for this reason, many researchers have used various numerical methods to solve fuzzy linear systems. in this paper, we define the concepts of midpoint a...

The growing availability of high-resolution satellite imagery provides an opportunity for identifying road objects. Most studies associated with road detection are scene-related and also based on the digital number of each pixel. Because images can provide more details (including color, size, shape, and texture), object-based processing is more advantageous. Therefore, in this paper, to handle ...

In this paper we present a comparison of two fuzzy-control approaches that were developed for use on a non-linear single-input singleoutput (SISO) system. The first method is Fuzzy Model Reference Learning Control (FMRLC) with a modified adaptation mechanism that tunes the fuzzy inverse model. The basic idea of this method is based on shifting the output membership functions in the fuzzy contro...

Fuzzy logic controls and neuro-fuzzy controls are accustomed to increase the performance of air conditioning system. In this paper, we are trying to provide the new design air conditioning system by exploitation two logics, namely fuzzy logic and neuro-fuzzy management. This paper proposes a set of rule and uses 2 inputs specifically temperature and humidness and 4 outputs specifically compress...

One of the advantages systems based on fuzzy logic (fuzzy systems) is possibility a soft switch from one set values input parameters system to another, when different conclusions are drawn for sets these values. A type 2 direct generalization an ordinary set. In this paper, we review some branches theory type-2 and systems. We discuss operations sets, relations, centroids describe functional re...

The purpose of this paper is, to describe a work-in process for application of distributed agency methodology to multi-dimensional preference model into a complex social system. This paper shows a study case focused on a modeling system for decision-making on cognitive structure religious affiliation preference. A type-2 neurofuzzy approach is used to configure cognitive rules into an agent to ...

The main objective of this study is to provide a valid and effective approach for the design and development of an adaptive type-2 fuzzy controller (AT2FLC), based on the analysis of the nonlinear process dynamics and the use of an ANFIS technique for the optimization of the controller. The performance of the obtained AT2FLC, characterized by a few number of rules, is higher than the performanc...