In this paper we design a state-feedback controller for the nonlinear benchmark problem. Our approach relies on the use of Takagi-Sugeno fuzzy models to approximate the nonlinear system. Once €he fuzzy model is obtained, we develop a guaranteed-cost framework to design the controller using Linear Matrix Inequality methods and recently obtained relaxed stability conditions. We show that our prop...

A class of fuzzy Cohen-Grossberg neural networks with distributed delay and variable coefficients is discussed. It is neither employing coincidence degree theory nor constructing Lyapunov functionals, instead, by applying matrix theory and inequality analysis, some sufficient conditions are obtained to ensure the existence, uniqueness, global attractivity and global exponential stability of the...

In this paper, a linear optimization problem is investigated whose constraints are defined with fuzzy relational inequality. These constraints are formed as the intersection of two inequality fuzzy systems and Schweizer-Sklar family of t-norms. Schweizer-Sklar family of t-norms is a parametric family of continuous t-norms, which covers the whole spectrum of t-norms when the parameter is changed...

The paper presents the problem of decentralized state feedback control for nonlinear interconnected systems with time-varying delay in both states and inputs which is composed by a number of Takagi-Sugeno (T-S) fuzzy bilinear subsystems with interconnections. Based on the Lyapunov criterion and the parallel distribute compensation scheme, the delay-dependent stabilization sufficient conditions ...

This paper focuses on the problem of Guaranteed cost control of uncertain T-S fuzzy systems. Based on observer design, the guaranteed cost output feedback control law which guarantees that the closed-loop uncertain T-S fuzzy system is robustly asymptotically stable is proposed. By utilizing the Lyapunov function together with the linear matrix inequality (LMI) approach and free weighting matrix...

Alternative LMI Conditions for Takagi-Sugeno Systems Via Fuzzy Lyapunov Function This paper deals with the stability analysis and control design for continuous Takagi-Sugeno fuzzy systems in a linear matrix inequality (LMI) framework. New LMI stability conditions are obtained by applying a relaxation strategy in a recently proposed fuzzy Lyapunov function. In these new LMI stability conditions,...

In this pape, a class of nonlinear time-delay systems based on the Takagi-Sugeno (T-S)fuzzy model is defined. We investigate the delay-independent stability of this model. A model-based fuzzy stabilization design utilizing the concept of the so-called “parallel distributed compensation” (PDC) is employed. The main idea of the controller design is to derive each control rule to compensate each r...

In this paper, we propose new sets of criteria for exponential robust stability of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. The L2−L∞ approach is applied to obtain new sets of stability criteria, under which T-S fuzzy Hopfield neural networks reduce the effect of external input to a prescribed level. These sets of criteria are presented based on the matrix norm and linear matrix ineq...

The Takagi-Sugeno (T-S) fuzzy multiple-variable integral control system with fuzzy state observer is designed for the coordinated control of multi-input-multi-output (MIMO) nonlinear boilerturbine system whose operating points vary within a wide range. Linear models are first derived from the original nonlinear model on several operating points. Next the fuzzy multi-variable integral controller...

This paper proposes a method for solving linear programming problems where all the coefficients are, in general, fuzzy numbers. We use a fuzzy ranking method to rank the fuzzy objective values and to deal with the inequality relation on constraints. It allows us to work with the concept of feasibility degree. The bigger the feasibility degree is, the worst the objective value will be. We offer ...