Fault sensor diagnosis with Takagi-Sugeno approach design applied for DFIG wind energy systems

Abstract

This paper investigates the problem of fault detection and isolation (FDI) design for nonlinear Takagi-Sugeno (T-S) models with measurable premise variables. The provided approaches are easily formulated in terms of Linear Matrix Inequalities (LMI) problem, based on Lyapunov theory. This latter introduces “virtual” dynamics both in the output error and the observer gain matrices. The strategy is illustrated using a non-linear model of a doubly fed induction generator (DFIG) for a wind turbine, affected by current sensor faults. In order to illustrate the applicability and the effectiveness of the proposed approaches.