This paper outlines two contributions to stability analysis of fuzzy systems: knowledge of the membership function shape (actually, constraints on the membership function values) and polynomial approaches. Both ideas reduce the conservativeness in the stability analysis of a nonlinear system when expressed as a fuzzy model by using membership shape information and by allowing a more general cla...

The paper deals with a recently proposed approach to combining classifiers by means of fuzzy aggregation. The approach relies on the quasi-Sugeno integral and on the t-conorm integral as a generalization of the Choquet and Sugeno integral, which have been used for combining classifiers so far. New theoretical development is presented, in particular a proposition concerning the λ measures used i...

Over the past two decades, there has been a rapidly growing interest in approximating a nonlinear system by a Takagi-Sugeno (T-S) fuzzy model (Takagi & Sugeno, 1985). In general, this model is represented by using a set of fuzzy rules to describe a global nonlinear system in terms of a set of local linear models which are smoothly connected by fuzzy membership functions. Based on the T-S fuzzy ...

This paper concerns the use of fuzzy structures to model linear dynamic systems. A systematic method is proposed to generate the rules and also select the antecedent and consequent membership functions directly from the mathematical expression. The procedure is applied to the Takagi-Sugeno-Kang fuzzy structures and later adapted to the Mamdani fuzzy structures. It is shown that the Mamdani stru...

Mamdani and Takagi-Sugeno fuzzy controllers were prepared. The controllers were designed using Fuzzy Logic Toolbox. The membership functions and rules were used as design tools that give opportunity to model a control surface and controller properties. The control system of d.c. (direct current) motor drive with two feedback loops is considered. First loop is used for stabilization of armature ...

This paper proposes a fuzzy model for predicting nonlinear behaviour of smart structures. The parameters of the fuzzy model are trained using the backpropagation neural network and least squares algorithms. To demonstrate the effectiveness of the proposed Takagi-Sugeno (TS) fuzzy model, a structure equipped with magnetorheological (MR) dampers is constructed and investigated. Various levels of ...

Robust pole placement in a LMI region for Takagi-Sugeno (Takagi & Sugeno 1985) fuzzy models is presented. The objective is to find a set of Linear Matrix Inequalities in order to ensure that the linear models poles remain in a specified region of the complex plane, even in presence of model uncertainties. As an illustration, the obtained conditions are applied to the spacing policy control of a...

Fuzzy set theory and fuzzy logic are the convenient tools for handling uncertain, imprecise, or unmodeled data in intelligent decision-making systems. The utility of fuzzy logic in system controls domain is presented in the context of a mobile robot navigation control application. The Takagi-Sugeno controller is a fuzzy model capable of approximating a wide class of nonlinear systems by decompo...

The purpose of this paper is to study the description of power system QV curves by using the method of fuzzy modeling for analysis of voltage stability. Voltage instability of power system comes from increasing load rapidly, and causes bus voltage to drop. When voltage is out of control and it can be voltage collapse. The QV curve can identify voltage stability limit, and it determine robustnes...