# Height Control System for Wind Turbines Based on Critical Wind Speed Calculation
## 2 Related Work and State of the Art  
Research in the field of automatic control systems and the optimization of wind turbine operations is currently actively developing, as evidenced by numerous publications in scientific journals. Below are the reviews of the most significant work, highlighting their achievements, limitations, and useful aspects for this study. Vertical-axis wind turbines (VAWTs) encounter challenges such as turbulent wind flows near the ground, leading to inconsistent wind speeds and fluctuating loads on the blades. The Onipko rotor, as a vertical-axis wind turbine, requires specific control strategies to manage its unique structural dynamics under varying wind conditions. They also face cyclic loading due to the blades experiencing different wind conditions during rotation, causing material fatigue. To address these issues, Model Predictive Control (MPC) has been proposed for power regulation and turbine positioning. This control system ensures good performance and structural stability by directly controlling the tilt angle, blade pitch angle, and generator torque [11]. Simulations based on OpenFAST and Simulink have shown MPC's superiority over traditional PID controllers in some aspects, such as increased control accuracy and reliability. However, implementing MPC comes with significant challenges compared to PID controllers. MPC requires more complex algorithms, higher computational resources, and more sophisticated tuning processes, which can be difficult to implement in practical applications [12]. Moreover, these systems result in significantly higher capital and operational costs. Capital costs arise from the need for advanced computational infrastructure and hardware capable of supporting the high demands of real-time processing. Additionally, operational costs are driven by the continuous need for maintenance and skilled personnel to handle the complexity of MPC algorithms [13]. On the other hand, PID controllers provide a more practical and economically feasible solution, especially for resource-constrained environments. Their ease of implementation, lower computational requirements, and minimal need for complex tuning make PID controllers an attractive choice for many wind turbine applications, including systems like the Onipko rotor. While MPC can provide superior performance in specific cases, PID controllers have proven to offer a reliable and cost-effective solution, particularly when long-term economic impacts such as the total cost of ownership, scalability, and operational reliability are considered [14]. On the other hand, traditional PID controllers have significant advantages, including ease of implementation, lower computational resource requirements, and straightforward tuning. This makes PID controllers a practical and cost-effective solution for many applications, including controlling the Onipko rotor during strong wind events, ensuring system reliability, and reducing the risk of component failure. PID controllers have proven themselves in the industry due to their reliability and effectiveness under a wide range of conditions [15]. Their simplicity allows for easy system integration and maintenance, making them a more practical and cost-effective solution for many applications than an MPC system. The article published in [16] addresses the challenges of ensuring reliability, safety, and efficiency in wind turbine control. While advanced methods like adaptive and predictive control can optimize performance and reduce maintenance costs, they demand significant computational power. This computing power is crucial because it enables the real-time processing of complex algorithms, ensuring timely responses to changing conditions. However, the high computational requirements, along with the need for substantial initial investments and skilled personnel, can limit the practical application of these advanced methods, especially in resource-constrained environments. The study published in [17] focuses on control strategies for wind turbine components using sensor-based systems.