Learning the Riccati solution operator for time-varying LQR via Deep Operator Networks

Researchers propose using deep operator networks to learn a surrogate for solving Riccati equations in LQR control problems, replacing repeated numerical integration with a single offline training stage. The approach trades computational cost during deployment for upfront learning, with theoretical guarantees on control performance across system families.

MentionsDeep Operator Networks · Linear Quadratic Regulator · Riccati equation

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