SABO optimization algorithm-based backstepping controller for DSIG within a wind turbine system

Tuning the PI and backstepping (BS) controllers is a critical issue for ensuring good tracking performance and stable operation of the wind turbine based on dual-stator induction generator (WT-DSIG) systems. However, no existing research has yet comprehensively tuned the control parameters. Therefore, this paper proposes an innovative tuning method using the subtraction-average-based optimizer (SABO) to ensure optimal PI and backstepping controller parameters tuning. The optimally tuned controllers-based field-oriented control (FOC) scheme is applied for a WT-DSIG system. This research aims to offer an easy and effective method for optimal tuning of the control parameters, which contributes to improving the control performance, hence the WT-DSIG system’s stability. The proposed method is superior to the existing techniques, as it uses the SABO, a metaheuristic stochastic algorithm, to simultaneously optimize the natural frequencies of the flux, speed, and current PI controllers and the backstepping controller’s gains. To assess the effectiveness of the proposed control approach, a hardware-in-the-loop (HIL) implementation is carried out using the PLECS/RT-Box real-time simulator. The HIL findings through comparative study further confirm the superiority of the optimally designed controllers over the conventional techniques, highlighting significant enhancements in dynamic, steady state, THD, and time-integral performance criteria, ISE, and IAE.