Hybrid type-2 fuzzy backstepping control of doubly fed induction generator for wind energy conversion systems

In this work, two new hybrid control techniques combining Lyapunov theory (backstepping) and artificial intelligence (fuzzy logic type 1 and 2) have been developed for a wind energy conversion system (WECS) based on a double fed induction generator (DFIG). The main objective of this hybridisation is to ensure the adaptation of the gains in backstepping control by the regulators of type 1 and type 2, and to achieve instantaneous, precise, and continuous control of the active and reactive power exchanged with the utility grid by a doubly fed induction generator in a wind energy conversion system, our approach guarantees robustness and stability, ensuring high efficiency and optimal production quality of our WECS. In addition, an in-depth comparative study between these developed controllers is also the focus of this paper. The aim of this study is to compare the two new control techniques with the previously introduced backstepping control technique to highlight the performance of each. This comparative study is based on a series of tests during transient and steady-state operation of the system under the same conditions, namely, a qualitative comparison aimed at comparing response times and reference tracking capabilities; a quantitative comparison based on error and time as two important metrics that must be considered simultaneously; and, finally, a robustness comparison based on parameter variation of the system. The results obtained will show which of the two hybrid controllers is the best and most efficient in our system.