In this paper, the operation of a fuzzy predictive filter used to provide high robustness against feedback signal noise in a fuzzy logic (FL)-based angle estimation algorithm for the switched reluctance motor is described. The fuzzy predictive filtering method combines both FL-based time-series prediction, as well as a heuristic knowledge-based algorithm to detect and discard feedback signal er...

W. Senn1;2, M. Jakob2, K. Wyler2, J. Kleinle2, H.-R. L uscher3, H. Mey2, L. M uller2 Abstract | Methods of fuzzy logic are commonly used to model a complex system by a set of rules provided by experts. But fuzzy methods can also be applied to the reverse problem: given the inputoutput behavior of a system, what are the rules which are governing that behavior. We introduce this reengineering m...

|A number of techniques have been introduced to construct fuzzy models from measured data. Most attention has been focused on multiple-input, single-output (MISO) systems. This article concentrates on the identi cation of multiple-input, multiple-output (MIMO) systems by means of product-space fuzzy clustering with adaptive distance measure (the Gustafson-Kessel algorithm). The MIMOmodel is rep...

In this study, we propose a novel method for modeling dynamic hysteresis. Hysteresis is a widespread phenomenon that is observed in many physical systems. Many different models have been developed for representing a hysteretic system. Among them, the Duhem model is a classical nonlinear dynamic hysteresis model satisfying the properties of hysteresis. The purpose of this work is to develop a no...

Volatility forecasting is a challenging task that has attracted the attention of market practitioners, regulators and academics in recent years. This paper proposes an evolving fuzzyGARCH approach to model and forecast the volatility of S&P 500 and Ibovespa indexes. The model comprises both the concept of evolving fuzzy systems and GARCH modeling approach in order to consider the principles of ...

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data modeling has been extensively investigated in various data models. Currently, huge amounts of electronic data are available on the Internet, and XML has been the de facto standard of information representation and exchange over the Web. This paper focuses on fuzzy XML data modeling, whic...

in this paper we study two important concepts, i.e. the direct andthe inverse limit of hyperstructures associated with fuzzy sets of type 2, andshow that the direct and the inverse limit of hyperstructures associated withfuzzy sets of type 2 are also hyperstructures associated with fuzzy sets of type 2.

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...

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...