Design of state observer for a class of non linear singular systems described by Takagi-Sugeno model

Abstract

In this paper, we propose a new method to design an observer for a class of non linear singular systems described by Takagi-Sugeno (TS) model, with measurable decision variables. The idea of the proposed approach is based on the singular value decomposition. The convergence of the state estimation error is studied using the Lyapunov theory and the stability conditions are given in terms of Linear Matrix Inequalities (LMIs). Finally, an example is given to illustrate the proposed approach.

Design Of Observer Based Quasi Decentralized Fuzzy Load Frequency Controller for Inter Connected Power System

“…However there is no generalized procedure for the design of estimators for nonlinear systems as it involves high computational costs. One such model which facilitates the stability analysis and observer design can be represented by Takagi-Sugeno (TS) fuzzy model [11], a special dynamic nonlinear model.…”

Controllability of singular linear systems by Legendre wavelets

“…They are usually simplified or approximated by nonsingular models because there is still lacking of efficient tools to tackle problems related to such systems. The structural analysis of linear singular systems, using either algebraic or geometric approach, has attracted considerable attention from many researchers during the last three decades (see, e.g., [1][2][3]).…”

Observer Design for a Class of Nonlinear Descriptor Systems: A Takagi-Sugeno Approach with Unmeasurable Premise Variables

“…The T-S fuzzy observer problems for dynamic T-S fuzzy models described by ordinary differential equations (ODEs) with measurable and unmeasurable premise variables are studied in [10][11][12][13][14][15][16][17][18][19][20]. Concerning nonlinear descriptor systems described by T-S descriptor models the problem of fuzzy observer design has been widely investigated; see, for instance, [21][22][23][24][25]. The aim of this paper is to give a fuzzy observer design to a class of fuzzy descriptor systems permitting to estimate the unknown state without the use of an optimization algorithm.…”