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A historical perspective of adaptive control and learning
This article provides a historical perspective of the field of adaptive control over the past
seven decades and its intersection with learning. A chronology of key events over this large …
seven decades and its intersection with learning. A chronology of key events over this large …
State estimation of the Stefan PDE: A tutorial on design and applications to polar ice and batteries
The Stefan PDE system is a representative model for thermal phase change phenomena,
such as melting and solidification, arising in numerous science and engineering processes …
such as melting and solidification, arising in numerous science and engineering processes …
[KNYGA][B] Traffic congestion control by PDE backstep**
This book explores the development of PDE (partial differential equation) backstep**
controllers for the suppression of stop-and-go instabilities and oscillations in congested …
controllers for the suppression of stop-and-go instabilities and oscillations in congested …
A stochastic model for stop-and-go phenomenon in traffic oscillation: On the prospective of macro and micro traffic flow
J Wen, L Hong, M Dai, X **
V Alleaume, M Krstic - IEEE Transactions on Automatic Control, 2024 - ieeexplore.ieee.org
For the quite extensively developed PDE backstep** methodology for coupled linear
hyperbolic PDEs, we provide a generalization from finite collections of such PDEs, whose …
hyperbolic PDEs, we provide a generalization from finite collections of such PDEs, whose …
Mitigating stop-and-go traffic congestion with operator learning
This paper presents a novel neural operator learning framework for designing boundary
control to mitigate stop-and-go congestion on freeways. The freeway traffic dynamics are …
control to mitigate stop-and-go congestion on freeways. The freeway traffic dynamics are …
Neural operator approximations of backstep** kernels for 2× 2 hyperbolic PDEs
Deep neural network approximation of nonlinear operators, commonly referred to as
DeepONet, has so far proven capable of approximating PDE backstep** designs in which …
DeepONet, has so far proven capable of approximating PDE backstep** designs in which …