In this paper, ‎the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented‎. ‎A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis‎. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...

Several scientific forecasting models for presidential elections have been suggested. However, most of these models are based on traditional statistics approaches. Since the system is linguistic, vague, and dynamic in nature, the traditional rigorous mathematical approaches are inappropriate for the modeling of this kind of humanistic system. This paper presents a combined neural fuzzy approach...

Abstract— The dynamic behavior of power systems is affected by the interactions between linear and nonlinear components. To analyze those complicated power systems, the linear approaches have been widely used so far. Especially, a synchronous generator has been designed by using linear models and traditional techniques. However, due to its wide operating range, complex dynamics, transient perfo...

This paper describes a neuro-fuzzy modeling framework for predicting the properties of ashes originated from combustion processes for electric generation. The prediction problem is tackled by means of a neuro-fuzzy system in which a neural network and a fuzzy system are combined in a fused architecture, so that the structure and the parameters of the fuzzy rule base are determined via a two-pha...

Fuzzy modeling of high-dimensional systems is a challenging topic. This paper proposes an effective approach to data-based fuzzy modeling of high-dimensional systems. An initial fuzzy rule system is generated based on the conclusion that optimal fuzzy rules cover extrema [8]. Redundant rules are removed based on a fuzzy similarity measure. Then, the structure and parameters of the fuzzy system ...

Fuzzy cognitive map is a powerful modeling tool. It has several desirable properties on control. In this paper, we utilize the feature and the inference mechanism of fuzzy cognitive map, and present a control method, which study combines control theory with fuzzy cognitive map theory. The causal relationship of variables is constructed by online learning or offline learning, the values of contr...

ObjectStab is a general purpose simulation tool for power system stability studies developed by Modelica which is an object-oriented modeling language. It provides enough modeling flexibility to allow addition or modification of new power system components. This paper describes an incorporated use of fuzzy logic toolbox in Matlab/Simulink and ObjectStab library to enhance the application of thi...

This paper focus several stability issues regarding the modeling of the dynamics of qualitative real world systems, and the ability of Fuzzy Cognitive Maps and Rule -Based Fuzzy Cognitive Maps to provide a faithful modeling in what concerns the stability properties of those systems. It also introduces the concept of Intrinsic Stability as a necessary property of qualitative system dynamics mode...

in this study, we offer a general view at the area of fuzzy modeling and fuzzymodels, identify the visible development phases and elaborate on a new and promisingdirections of system modeling by introducing a concept of granular models. granularmodels, especially granular fuzzy models constitute an important generalization of existingfuzzy models and, in contrast to the existing models, generat...