Fixed Horizon Linear Quadratic Covariance Steering in Continuous Time with Hilbert-Schmidt Terminal Cost
NeutralArtificial Intelligence
A recent study has tackled the fixed horizon linear quadratic covariance steering problem in continuous time, introducing a novel approach that utilizes Hilbert-Schmidt norm for measuring terminal costs. This research is significant as it not only formulates the necessary conditions of optimality but also presents a solution through a matricial recursive algorithm. Such advancements in mathematical optimization can have implications in various fields, including control theory and engineering, enhancing our ability to manage complex systems effectively.
— Curated by the World Pulse Now AI Editorial System


