Tracking Control

Tracking control, aiming to precisely guide a system along a desired trajectory, is a crucial area in robotics and control systems. Current research emphasizes improving controller robustness and efficiency through methods like adaptive control for friction compensation, reinforcement learning with curriculum learning or symmetry exploitation to accelerate training, and model-free approaches using machine learning such as reservoir computing. These advancements address challenges posed by system nonlinearities, uncertainties, and computational constraints, impacting diverse applications from robotic surgery and manipulation to autonomous vehicles and micro-robotics.