Adaptive Control

Adaptive control focuses on designing controllers that automatically adjust their parameters to maintain desired system performance despite uncertainties and disturbances. Current research emphasizes robust adaptive control methods, often incorporating model reference adaptive control (MRAC), reinforcement learning (RL), and neural networks (including neural operators) to handle complex nonlinearities and unknown dynamics in diverse applications. This field is crucial for enhancing the safety, efficiency, and adaptability of autonomous systems, from robotic manipulators and drones to underwater vehicles and even construction project management.