Networked Predictive Control

Networked predictive control (NPC) addresses the challenges of controlling systems with geographically distributed components connected via communication networks, aiming to maintain stability and performance despite network delays and packet loss. Current research focuses on developing robust control algorithms, such as distributed policy gradient methods and model predictive control (MPC) strategies, that compensate for network uncertainties and leverage limited communication bandwidth. This field is significant for enabling the control of complex, spatially distributed systems in various applications, including robotics and industrial automation, by providing efficient and reliable control solutions in the face of inherent network limitations.