4 papers
DeepONet-LSTM Neural Operator for Output Feedback Control of Reaction Diffusion PDEs
Jing Zhang, Jie Qi, Linglong Jiang
This paper presents a neural operator-based approach for the output feedback boundary stabilization of reaction diffusion PDEs. The classical output feedback backstepping design re…
Neural Operator Feedback for a First-Order PIDE with Spatially-Varying State Delay
Jie Qi, Jiaqi Hu, Jing Zhang +1
A transport PDE with a spatial integral and recirculation with constant delay has been a benchmark for neural operator approximations of PDE backstepping controllers. Introducing a…
Neural Operator based Reinforcement Learning for Control of first-order PDEs with Spatially-Varying State Delay
Jiaqi Hu, Jie Qi, Jing Zhang
Control of distributed parameter systems affected by delays is a challenging task, particularly when the delays depend on spatial variables. The idea of integrating analytical cont…
Neural Operators for PDE Backstepping Control of First-Order Hyperbolic PIDE with Recycle and Delay
Jie Qi, Jing Zhang, Miroslav Krstic
The recently introduced DeepONet operator-learning framework for PDE control is extended from the results for basic hyperbolic and parabolic PDEs to an advanced hyperbolic class th…