activity
20172026
most citedA Scaled Smart City for Experimental Validation of Connected and Automated Vehicles

7 citations · 13 across the 16 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

eess.SY2024★ 1 cited

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…

cs.RO2024

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…

eess.SY2024

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…

eess.SY2024

PDE Control Gym: A Benchmark for Data-Driven Boundary Control of Partial Differential Equations

Luke Bhan, Yuexin Bian, Miroslav Krstic +1

Over the last decade, data-driven methods have surged in popularity, emerging as valuable tools for control theory. As such, neural network approximations of control feedback laws,…

eess.SY2024★ 2 cited

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…

eess.SY2024★ 3 cited

Gain Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation

Maxence Lamarque, Luke Bhan, Rafael Vazquez +1

To stabilize PDE models, control laws require space-dependent functional gains mapped by nonlinear operators from the PDE functional coefficients. When a PDE is nonlinear and its "…

eess.SY2024

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…