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...

Adaptive linearization controllers have been shown to have nice performance. However, two functions in the controllers are derived from the considered system. In other words, they can only work for known systems. In this paper, the considered dynamic nonlinear model can be unknown. Next, we proposed an affined Takagi-Sugeno-type (TS-type, for short) fuzzy modeling approach to model those two un...

ABSTRACT: This article presents a rule-based fuzzy model for the identification of nonlinear MISO (multiple input, single output) systems. The presented method of fuzzy modeling consists of two parts: (1) structure modeling, i.e., the determination of the number of rules and input variables involved respectively, and (2) parameter optimization, i.e., the optimization of the location and form of...

Abstract: This paper focuses on the Fuzzy Frequency Response: Definition and Analysis for Uncertain Dynamic Systems. In terms of transfer function, the uncertain dynamic system is partitioned into several linear sub-models and it is organized into Takagi-Sugeno (TS) fuzzy structure. The main contribution of this approach is demonstrated, from a Theorem, that fuzzy frequency response is a bounda...

System identification is the task of developing or improving a mathematical description of dynamic systems from experimental data (Ljung (1999); Söderström & Stoica (1989)). Depending on the level of a priori insight about the system, this task can be approached in three different ways: white box modeling, black box modeling and gray box modeling. These models can be used for simulation, predic...

This paper considers the fuzzy modeling and robust fuzzy variable control for quadrotor in uncertain environment. The nonlinear system of quadrotor is firstly analyzed in this paper by utilizing laws of motion and force. Then, a Takagi-Sugeno (T-S) fuzzy model is achieved to approximate the system. LMI method is used to acquire an improved sliding surface. On this basis, a fuzzy variable struct...