Inverse fuzzy process model based direct adaptive control. [2] J. Abonyi and R. Babuška. Local and global identification and interpretation of parameters in Takagi–Sugeno fuzzy models. In Proceed-[3] J. Abonyi and R. Babuška. Local and global identification and interpretation of parameters in Takagi–Sugeno fuzzy models. In Proceed-tification and control of nonlinear systems using fuzzy Hammerst...

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This paper deals with Takagi-Sugeno modelling and control of nonholonomic mobile robots in the case when the measurements are given by the camera. The measurements in such case are difficult to deal with: they are given only in discrete time samples, usually they are delayed, a high-level noise is present on the measurements. The nonlinear tracking error-model is solved analytically under the p...

An extension of the time-dependent Takagi-Taupin theory to 'optical phonon'-type distortions is presented. By splitting the susceptibility into the contributions from each atom in a unit cell, modifications to the structure factor as well as lattice parameter are taken into account. The result is a compact, surprisingly simple, equation with a strong formal similarity to the classical Takagi-Ta...

In this paper, we introduce a robust state feedback controller design using Linear Matrix Inequalities (LMIs) and guaranteed cost approach for Takagi-Sugeno fuzzy systems. The purpose on this work is to establish a systematic method to design controllers for a class of uncertain linear and non linear systems. Our approach utilizes a certain type of fuzzy systems that are based on Takagi-Sugeno ...

We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditi...

In this paper, we present two results concerning the fuzzy modeling and control of nonlinear systems. The first result is on the approximation of smooth nonlinear dynamical systems using linear Takagi-Sugeno fuzzy models. The second result is on the approximation of smooth nonlinear state-feedback controllers using the the so-called parallel distributed compensation (PDC) controller. Both resul...