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Found 2 papers, 2 papers with code
Adaptive Neural-Operator Backstepping Control of a Benchmark Hyperbolic PDE
This requires an adaptive approach to PDE control, i. e., an estimation of the plant coefficients conducted concurrently with control, where a separate PDE for the gain kernel must be solved at each timestep upon the update in the plant coefficient function estimate.
Gain Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation
The recently introduced neural operators (NO) can be trained to produce the gain functions, rapidly in real time, for each state value, without requiring a PDE solution.
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