14 citations · 17 across the 13 of their papers we have counts for
5 papers · 1 filter
Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems
Luke Bhan, Peijia Qin, Miroslav Krstic +1
Predictor feedback designs are critical for delay-compensating controllers in nonlinear systems. However, these designs are limited in practical applications as predictors cannot b…
Generalizable Motion Planning via Operator Learning
Sharath Matada, Luke Bhan, Yuanyuan Shi +1
In this work, we introduce a planning neural operator (PNO) for predicting the value function of a motion planning problem. We recast value function approximation as learning a sin…
Adaptive control of reaction-diffusion PDEs via neural operator-approximated gain kernels
Luke Bhan, Yuanyuan Shi, Miroslav Krstic
Neural operator approximations of the gain kernels in PDE backstepping has emerged as a viable method for implementing controllers in real time. With such an approach, one approxim…
Adaptive Neural-Operator Backstepping Control of a Benchmark Hyperbolic PDE
Maxence Lamarque, Luke Bhan, Yuanyuan Shi +1
To stabilize PDEs, feedback controllers require gain kernel functions, which are themselves governed by PDEs. Furthermore, these gain-kernel PDEs depend on the PDE plants' function…
Moving-Horizon Estimators for Hyperbolic and Parabolic PDEs in 1-D
Luke Bhan, Yuanyuan Shi, Iasson Karafyllis +2
Observers for PDEs are themselves PDEs. Therefore, producing real time estimates with such observers is computationally burdensome. For both finite-dimensional and ODE systems, mov…