Robust fault tolerant control of DFIG wind energy systems with unknown inputs

This paper proposes a Fuzzy Dedicated Observers (FDOS) method using a Nonlinear Unknown Input Fuzzy Observer (UIFO) with a Fuzzy Scheduler Fault Tolerant Control (FSFTC) algorithm for fuzzy Takagi-Sugeno (TS) systems subject to sensor faults, parametric uncertainties, and time varying unknown inputs. FDOS provide residuals for detection and isolation of sensor faults which can affect a TS model. The TS fuzzy model is adopted for fuzzy modeling of the uncertain nonlinear system and establishing fuzzy state observers. The concept of Parallel Distributed Compensation (PDC) is employed to design FSFTC and fuzzy observers from the TS fuzzy models. TS fuzzy systems are classified into three families based on the input matrices and a FSFTC synthesis procedure is given for each family. In each family, sufficient conditions are derived for robust stabilization, in the sense of Taylor series stability and Lyapunov method, for the TS fuzzy system with parametric uncertainties, sensor faults, and unknown inputs. The sufficient conditions are formulated in the format of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through a wind energy system with Doubly Fed Induction Generators (DFIG) to illustrate the effectiveness of the proposed method.

► This approach is an extension of the previous work (Kamal et al.[20]).
► Fault tolerant controller can be designed such that the states are stable.
► Robust controller is computed in presence of sensor faults and unknown inputs.
► TS fuzzy systems classified into three families, design controller for each family.
► Maximization the power coefficient for a variable-speed wind energy systems.