Summary In this study, a fractional order fuzzy proportional‐integral‐derivative (FOFPID) controller is designed for load frequency control of four‐area interconnected power systems. The model of system consists of three reheat thermal turbine units (Area1, Area2, and Area3) and one hydro power plant (Area4). Therefore, the proposed controller (with same and different parameters) is employed for the first three zones, and different controller parameters are considered for Area4 due to existence of hydro turbine. In order to minimize frequency and power tie‐line deviations in the system, biogeography‐based optimization (BBO) algorithm is utilized to tune controller parameters. Finally, the proposed technique is compared with three different controllers including PID, fuzzy PID (FPID), and fractional order PID. For a fair comparison, the parameters of aforesaid controllers are also tuned by BBO algorithm. The results of different simulation cases indicate that the FOFPID controller has a superior performance and transient response compared with the other approaches against various load disturbances.

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The current study presented a novel single-input control technique, called the single-input interval type-2 fractional-order fuzzy (SIT2FOF) controller. This controller is suitable for the control problems in which the plant deals with hard external disturbance and model uncertainties. Fractional calculus and interval type-2 fuzzy sets are considered as two seminal parts of the SIT2FOF controller which provide robust control performance. In addition, single-input interval type-2 fuzzy (SIT2F) sets in the structure of the proposed controller reduce computational efforts and the number of tuning parameters. Accordingly, the controller can be implemented and tuned easily. Thus, the control problem of an automatic voltage regulator in a power system and a Kubota M110X tractor active suspension system were considered as case studies to validate the suggested method. To this end, simulations were performed in three scenarios, followed by comparing the proposed technique in each scenario with single-input type-1 fuzzy (ST1F), single-input type-1 fractional-order fuzzy (ST1FOF), and single-input interval type-2 fuzzy (SIT2F) controllers. The results revealed that the SIT2FOF control technique can significantly handle external disturbances and model uncertainties more efficiently compared to the other controllers.