Adaptive control is a branch of control theory that involves designing controllers that can adjust their parameters or structure in real-time to cope with uncertainties, disturbances, and changing dynamics in a system. The goal of adaptive control is to achieve stable and optimal performance in the presence of these uncertainties, without the need for manual tuning or redesign of the controller. Adaptive control algorithms typically use online identification techniques to estimate the system's parameters and update the controller accordingly. This research area is widely applied in various fields, including aerospace, robotics, automotive, and process control, to improve the performance and robustness of control systems.