The main objective of this paper is to expound the singular-value-decomposition (SVD)-based reduction technique proposed to single-input–single-output Takagi-Sugeno (TS) fuzzy models to multivariable cases. The use of higher order singular value decomposition is proposed in this paper for the complexity reduction of multiple-input–single-output TS fuzzy model approximation. A detailed illustrat...

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...

In this correspondence a new simple strategy for reducing the conservativeness in stability analysis of continuous-time Takagi–Sugeno fuzzy systems based on fuzzy Lyapunov functions is proposed. This new strategy generalizes previous results. © 2009 Elsevier Ltd. All rights reserved.

Dynamic Takagi-Sugeno fuzzy models are not always easy to interpret, in particular when they are identiied from experimental data. Ideally, it is desirable that a dynamic Takagi-Sugeno fuzzy model should give accurate global nonlinear prediction, and at the same time that its local models are close approximations to the local linearizations of the nonlinear dynamic system. The latter is importa...

Dynamic Takagi-Sugeno fuzzy models are not always easy to interpret, in particular when they are identified from experimental data. Ideally, it is desirable that a dynamic Takagi-Sugeno fuzzy model should give accurate global nonlinear prediction and at the same time that its local models are close approximations to the local linearizations of the nonlinear dynamic system. The latter is importa...

Abstract. In this paper an algorithm for neuro-fuzzy identification of multivariable discrete-time nonlinear dynamical systems is proposed based on a decomposed form as a set of coupled multiple input and single output (MISO) Takagi-Sugeno (TS) neuro-fuzzy networks. An on-line scheme is formulated for modeling a nonlinear autoregressive with exogenous input (NARX) neuro-fuzzy structure from sam...

The use of Linear Matrix Inequalities and Common Quadratic Lyapunov Functions is a powerful and commonplace tool for Takagi-Sugeno fuzzy controlled system analysis and synthesis. However, in practice, few practical and performing results are available when the subsystems exhibit different input matrices, because of the strong coupling between the subsystems/subcontrollers. In this paper, this c...

We study the filter design problem for Takagi-Sugeno fuzzy systems which are subject to norm-bounded uncertainties in each subsystem. As we know that the Takagi-Sugeno fuzzy linear systems can be used to represent smooth nonlinear systems, the studied plants can also be uncertain complex systems. We suppose to design a filter with the order of the original system which is also dependent on the ...