A large class of nonlinear systems can be well approximated by Takagi-Sugeno fuzzy models, for which methods and algorithms have been developed to analyze their stability and to design observers and controllers. However, results obtained for Takagi-Sugeno fuzzy models are in general not directly applicable to the original nonlinear system. In this paper, we investigate what conclusions can be d...

The paper is concerned with robust stability criteria for Takagi- Sugeno (T-S) fuzzy systems with distributed delays and time delay in the leakage term. By exploiting a model transformation, the system is converted to one of the neutral delay system. Global robust stability result is proposed by a new Lyapunov-Krasovskii functional which takes into account the range of delay and by making use o...

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 ...

Uncertainty has been treated in science for several decades. It always exists in real systems. Probability has been traditionally used in modeling uncertainty. Belief and plausibility functions based on the Dempster–Shafer theory ~DST! become another method of measuring uncertainty, as they have been widely studied and applied in diverse areas. Conversely, a fuzzy set has been successfully used...

Takagi-Sugeno (TS) fuzzy modeling and control techniques are applied to the classical nonlinear Ball and Beam problem. The nonlinear model is segmented to different local linear models. Local controllers are hence designed using LMI theory for achieving a robust control behavior for ball position. TS fuzzy modeling is applied to generate suitable fuzzy models, and the associated controllers. Us...

Fuzzy systems can provide us with universal approximation models of deterministic input–output relationships, but in the stochastic environment few achievements related to the subject have so far achieved. In the paper a novel stochastic Takagi–Sugeno (T–S) fuzzy system is introduced to represent approximately existing randomness in many real-world systems. By recapitulating the general archite...

This paper suggests a new stability analysis theorem dedicated to a class of fuzzy logic control systems. The fuzzy logic control systems consist of nonlinear Single Input-Single Output (SISO) discrete-time processes controlled by Takagi-Sugeno fuzzy logic controllers. The stability analysis is conducted on the basis of Lyapunov’s direct method with quadratic Lyapunov function candidates. The t...

Controller design strategy for Takagi-Sugeno (T-S) fuzzy systems is considered in the two-degree-of-freedom (TDOF) framework. Firstly, coprime factorization described in the state space formulas for T-S fuzzy systems is introduced based on a common Lyapunov function. Secondly, based on this coprime factorization, TDOF framework for LTI systems is extended to be applied to T-S fuzzy systems. Con...

Abstract: Recently, supervised artificial neural networks have obtained success to reveal and provide quantitative information concerning defects in TNDE (Thermographic NonDestructive Evaluation). Supervised neural networks may converge to local minimum and their training procedure are usually long. In this study, a neuro-fuzzy approach is applied to characterize subsurface defects in TNDE. Sim...