## 1 Introduction  
The control of electrical drives is a critical aspect of modern automation and industrial applications, where precision, stability, and efficiency are required [1; 2; 3]. Electrical drives, which include motors and their control systems, are integral to various industries, ranging from manufacturing to robotics and transportation. In industry, electrical drives are used to power machinery, robotic arms, and others, ensuring smooth and precise operation essential for high-quality and high-demand production. Right control of these drives allows for the control of complex processes, reducing downtime and increasing overall productivity. Especially in robotics, electrical drives enable precise movements and operations. This precision is very important for tasks such as assembly, welding, and handling. Advanced control systems in electrical drives ensure that robots can perform complex tasks with high accuracy and repeatability. Considering the transportation sector, electrical drives are widely used in electric vehicles, trains, and other forms of transportation [4; 5]. The ability to precisely control motor functions in EVs leads to better performance, extended range, and enhanced safety. An additional aspect that is often overlooked is working in critical conditions [3]. Moreover, electrical drives are also found in home appliance systems, and renewable energy applications such as wind turbines and solar tracking systems. In each of these applications, the control of electrical drives is essential for optimizing performance, improving energy efficiency, and maintaining system stability. When analyzing industrial systems, the dynamics of control and immunity to errors are required. Additionally, in recent years, attention has been paid to the energy consumption of actuator systems. However, the main problem that modern engineers have to deal with is the above-mentioned dynamics of technological processes and their control [1,6]. This quality is largely influenced by properties such as disturbances, which include unexpected changes or disruptions in the system and operating smoothly without sudden changes or oscillations, and it needs to accurately respond to the desired commands, which can affect the performance of the electrical drive. Overall, managing measurement noise and disturbances is crucial for examining the performance and reliability of electrical drives. This ensures that the drives can operate smoothly and accurately, which is essential for their applications. From a control engineering perspective, the dominant control structure is the so-called cascade structure. Taking into account the above-mentioned aspects of control system requirements, when designing the dynamics of electromechanical systems, one should focus on the time requirements of the electromechanical subsystems that make up the drive system. Very often, one encounters systems that contain a time delay of a significant value compared to the other time constants of the considered system dynamics. In cases where there is a significant time delay in a system, using a structure that incorporates a system model is usually considered to improve control performance. Two common approaches in such scenarios are the _Smith's Predictor_ (SP) and _Internal Model Control_ (IMC) [7,8]. The basic idea of the _Smith Predictor_ is to use a model of the system to predict future outputs. By incorporating this predictive model, the controller can compensate for the delay, allowing for more effective and timely control actions. Essentially, it anticipates the effect of the time delay and adjusts the control inputs accordingly. The other approach, IMC, also uses a model of the system within the controller. The key concept of IMC is that the controller contains a model of the process it is controlling. By comparing the actual process output with the output predicted by the model, the controller can make adjustments to minimize the differences. IMC is known for its robustness and ability to handle model inaccuracies and disturbances effectively.