Data-driven control is a research area that focuses on using data-driven methods, such as machine learning and data analytics, to develop control strategies for complex systems. This approach involves collecting and analyzing data from the system in order to improve its control performance, efficiency, and robustness. By leveraging data-driven techniques, researchers aim to create adaptive and intelligent control systems that can effectively handle uncertainty, disturbances, and nonlinear dynamics. This research area is particularly relevant in the context of advanced manufacturing, autonomous vehicles, robotics, and other high-tech applications where traditional control methods may not be sufficient.