This paper considers the problem of designing static output feedback controllers for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models. Based on linear matrix inequality technique, a new method is developed for designing fuzzy stabilizing controllers via static output feedback. Furthermore, the result is also extended to H∞ control. Examples are given to illustrate the effective...

This paper considers the robust stabilization problem for Takagi-Sugeno fuzzy systems with time-varying delays subject to input saturation. The purpose is the design of dynamic anti-windup fuzzy controllers ensuring convergence of all admissible initial states within the domain of attraction. Delay-dependent conditions for the existence of solutions to this problem are obtained. A simulation ex...

Similarity measures of intuitionistic fuzzy sets are used to indicate the similarity degree between intuitionistic fuzzy sets. Although several similarity measures for intuitionistic fuzzy sets have been proposed in previous studies, no one has considered the use of the Sugeno integral to define them. Since the Sugeno integral provides an expected-value-like operation, it can be a useful tool i...

Type-2 fuzzy logic systems are an area of growing interest over the last years. The ability to model uncertainties and to perform under noisy conditions in a better way than type-1 fuzzy logic systems increases their applicability. A new stable on-line learning algorithm for interval type-2 Takagi–Sugeno–Kang (TSK) fuzzy neural networks is proposed in this paper. Differently from the other rece...

Most of the recent research in the design of fuzzy controllers has been centered on automatic techniques using expert’s input-output data. The majority of these techniques rely on the use of Takagi-Sugeno type controllers and fuzzy-neural-network [3-5,11], fuzzy clustering and fuzzy partition approaches [1,2,6,7]. These controllers, however, are not fully-linguistic and the use of neural-networ...

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...

Sugeno-Weber family of t-norms and t-conorms is one of the most applied one in various fuzzy modelling problems. This family of t-norms and t-conorms was suggested by Weber for modeling intersection and union of fuzzy sets. Also, the t-conorms were suggested as addition rules by Sugeno for so-called  $lambda$–fuzzy measures. In this paper, we study a nonlinear optimization problem where the fea...

Since the 2-DOF rehabilitation robot actuated by pneumatic muscle actuators (PMAs) has highly nonlinear and time-varying behavior due to gas compression and nonlinear elasticity of bladder containers, it is difficult to achieve excellent control performance using classical control methods. Here, this study proposes a novel Takagi-Sugeno(T-S) fuzzy approach to improve tracking performance. The T...

An algorithm for real-time prediction of river stage dynamics using a Takagi-Sugeno fuzzy system is presented in this paper. The system is trained incrementally each time step and is used to predict onestep and multi-step ahead of river stages. The number of input variables that were considered in the analysis was determined using two statistical methods, i.e. autocorrelation and partial autoco...

This paper presents an adaptive fuzzy controller for a class of completely pure-feedback nonlinear systems. Takagi-Sugeno type fuzzy logic systems are used to approximate the unknown nonlinear functions. The controller synthesis is developed by the backstepping technique and the small gain approach. The closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB...