## 1 Introduction
In Erkol [10], optimal tuning of PID control was undertaken using ABC, PSO, GA, and the Ziegler-Nichols (ZN) method for attitude and hover control the quadrotor. Findings show that ABC and GA-based controllers provide the best performance in terms of integral absolute error (IAE) and root mean square error (RMSE). The ABC-based PID controller has a short settling time and low overshoot in roll and pitch motion, while the GA-based PID controller is the best in yaw and altitude motion. The worst performance is obtained using the ZN method. Some other papers related to the optimization-based controller can also be found [44; 45; 46; 47]. A metaheuristic algorithm called Grey Wolf Optimizer (GWO) has become increasingly popular among researchers in the optimization area. This popularity has risen due to the proven effectiveness and efficiency of the algorithm [48] in solving various optimization problems. This can be noted from the fact that GWO has been implemented in various applications such as economic dispatch problems, power system problems, gene classification problems, forecasting problems, etc. [PERSON], [PERSON] [49] proposed a hybrid GWO with a differential evolution (DE)-type mutation and crossover in solving the economic dispatch problem, which is nonlinear, non-convex, and discontinuous nature with various inequality and equality constraints. The GWO optimizer was hybridized so that the mutation and crossover were able to be performed. The result showed that the GWO was able to achieve the objective of the study. In another work by [PERSON], [PERSON] [50], the author used the GWO to find a solution to the dynamic economic load of dispatch (ELD) problem and a solution for the non-convex of an electric power system. The results were then compared to PSO, GA, BBO, and DE. Findings showed that the GWO achieved a better performance than the others. Additionally, the GWO also could solve the ELD problem with a faster convergence rate. [PERSON], [PERSON] [51] studied the GWO and minimized some reactive power losses to enhance the distribution system's voltage profile without violating the system constraints. A comparative study with the gravitational search algorithm (GSA) and bat algorithm (BA) was undertaken. It was found that the GWO gave a satisfactory performance than the others. The author concluded that the GWO is an effective method for power loss reduction problems by providing voltage enhancements and load ability improvements. In [PERSON] and [PERSON] [52], the GWO was used to optimize the dual unified power flow controller (UPFC) model for damping power oscillations system. The results were observed from various aspects, including undershoot, overshoot, time, and speed deviation, which lower the oscillation frequency and eventually enhance the stability to a large extent. [PERSON] and [PERSON] [53] proposed improving the GWO with the Powell local optimization method to solve the clustering problems. Since Powell's structure is known for its strong local optimization ability, the author embedded it to GWO as one of the local search operators. The proposed GWO was tested, and the result was compared to the well-known benchmarks. The proposed method gives an outstanding performance that led to future research. [PERSON], [PERSON] [54] proposed a binary GWO to select the optimal feature subset of the classification and maximize the accuracy. The individual steps start with binarization of the best three solutions, and then crossover is performed. For the capability of the GWO, the binary version showed better performance since the feature selected was of the best features. [PERSON], [PERSON] [55] used the GWO to optimize the PID controller's performance for a direct current (DC) motor's speed control. The GWO results are compared with ZN, PSO, and ABC. The result showed that the GWO outperformed the other in optimizing the DC motor's PID controller with a good transient response performance.