The identification of nonlinear systems operating in a stochastic environment is an important problem in various discipline science and engineering. Fuzzy modeling and especially the T-S fuzzy model draw the attention of several researchers in recent decades this is due to their potential to approximate highly nonlinear behavior. An algorithm allowing the identification of the premise and conse...

In this paper, a novel and unified control approach that combines intelligent fuzzy logic methodology with impulsive control is developed for controlling a class of chaotic systems. We first introduce impulses into each subsystem of T-S fuzzy IF-THEN rules and then present a unified T-S impulsive fuzzy model for chaos control. Based on the new model, a simple and unified set of conditions for c...

K e y w o r d s T o p o l o g y , C-scattered and scattered topological spaces. ('ompactness, Fuzzy perfect maps, S-paracompactness, S*-paracompactness. Fuzzy paracompactness. *-Fuzzy paracompactness. 1. I N T R O D U C T I O N The concept of C-sca t te red topological space has been defined by Telg{,rsky [1]. A space X is said to be C-sca t te red if each of its nonempty closed subspaces conta...

1 An approach to fuzzy control of nonlinear systems: Stability and design issues Wang, HO; Tanaka, K; Griffin, MF IEEE TRANSACTIONS ON FUZZY SYSTEMS 1029 STABILITY ANALYSIS AND DESIGN OF FUZZY CONTROL-SYSTEMS TANAKA, K; SUGENO, M FUZZY SETS AND SYSTEMS 1013 Fuzzy regulators and fuzzy observers: Relaxed stability conditions and LMI-based designs Tanaka, K; Ikeda, T; Wang, HO IEEE TRANSACTIONS ON...

In this paper, new observer design approaches are presented for TakagiSugeno (T-S) fuzzy models with measurement output noises. In order to decouple the measurement noise, an augmented fuzzy descriptor model is first constructed. Then a fuzzy descriptor proportional and derivative (PD) observer is developed. When the fuzzy subsystems have the same output matrices, another fuzzy descriptor obser...

This paper deals with the synthesis of fuzzy state feedback controller of induction motor with optimal performance. First, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy controller is designed to stabilise the induction motor and guaranteed a minimum disturbance attenuati...

Active Learning Method (ALM) is a soft computing method used for modeling and control based on fuzzy logic. All operators defined for fuzzy sets must serve as either fuzzy S-norm or fuzzy T-norm. Despite being a powerful modeling method, ALM does not possess operators which serve as S-norms and T-norms which deprive it of a profound analytical expression/form. This paper introduces two new oper...

Since the T-S fuzzy system can approximate any nonlinear system with arbitrary accuracy, it is also expected to be a suitable approach to observe the states of a stochastic nonlinear system. Up to date, a few state estimators for stochastic T-S fuzzy systems have been proposed and applied to various fields without rigorous proof. In this paper, we first derive a sufficient condition based on th...