Unknown Disturbance

Unknown disturbances in dynamical systems represent a significant challenge across diverse fields, from robotics and power systems to autonomous vehicles and neuromorphic computing. Current research focuses on developing robust control strategies and estimation techniques, employing methods like model predictive control, reinforcement learning (including deep reinforcement learning and federated learning), and machine learning for disturbance identification and mitigation. These advancements aim to improve the reliability and safety of complex systems operating in unpredictable environments, impacting fields ranging from industrial automation to renewable energy integration.