This article maidenly presents a resilient hybrid fractional-order controller (hy-FOC) comprised of fractional-order proportional-integral-derivative (FOPID) controller and fractional-order sliding mode controller (FOSMC) for frequency regulation of an islanded hybrid power system (HPS) integrated with a doubly-fed induction generator (DFIG)-driven wind power generator. The slime mould algorithm is applied to obtain near-optimum gains of the hy-FOC via the minimization of an integral error criterion. Moreover, a Luenberger disturbance observer (Dob) is designed to estimate uncertain plant disturbances and incorporate estimated output into the control law to alleviate chattering in the output of sliding mode controller (SMC). The acceptability and superiority of the proposed hy-FOC are established by performing an extensive comparative study with the results of PI-derivative (PID), SMC, FOPID, and FOSMC under diverse operating conditions (model uncertainties and uncertain external disturbances). The simulation results are presented and discussed to authenticate proficiency of the proposed resilient control methodology over its other integral-order and fractional-order counterparts. Governor dead-band and generation rate constraint (thermal unit) as a provenance of physical limitations are also considered in the model to show the proposed controller's effectiveness for handling the practical challenges. Lastly, the sensitivity and robustness of the proposed approach have been affirmed by varying system parameters between ±25% of nominal settings.

中文翻译：

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用于混合电力系统频率调节的观察者辅助弹性混合分数阶控制器

本文首次提出了一种由分数阶比例积分微分 (FOPID) 控制器和分数阶滑模控制器 (FOSMC) 组成的弹性混合分数阶控制器 (hy-FOC)，用于孤岛混合电力系统的频率调节。 HPS) 与双馈感应发电机 (DFIG) 驱动的风力发电机集成。通过最小化积分误差准则，应用粘液模算法来获得 hy-FOC 的近乎最佳增益。此外，设计了 Luenberger 干扰观测器 (Dob) 来估计不确定的设备干扰并将估计输出纳入控制律，以减轻滑模控制器 (SMC) 输出中的颤动。所提出的 hy-FOC 的可接受性和优越性是通过对 PI 导数 (PID)、SMC、FOPID 和 FOSMC 在不同操作条件（模型不确定性和不确定的外部干扰）下的结果进行广泛的比较研究来确定的。提出并讨论了仿真结果，以验证所提出的弹性控制方法对其其他整数阶和分数阶对应方法的熟练程度。模型中还考虑了作为物理限制来源的调速器死区和发电率约束（热单位），以显示所提出的控制器处理实际挑战的有效性。最后，通过在标称设置的 ±25% 之间改变系统参数，证实了所提出方法的灵敏度和稳健性。