activity
20142024
most citedDeep Learning of Delay-Compensated Backstepping for Reaction-Diffusion PDEs

9 citations · 24 across the 10 of their papers we have counts for

collaborators

10 papers

math.OC2024

Periodic Event-Triggered Boundary Control of Neuron Growth with Actuation at Soma

Cenk Demir, Mamadou Diagne, Miroslav Krstic

Exploring novel strategies for the regulation of axon growth, we introduce a periodic event-triggered control (PETC) to enhance the practical implementation of the associated PDE b…

math.OC20241 cited

Unbiased Extremum Seeking for PDEs

Cemal Tugrul Yilmaz, Mamadou Diagne, Miroslav Krstic

There have been recent efforts that combine seemingly disparate methods, extremum seeking (ES) optimization and partial differential equation (PDE) backstepping, to address the pro…

math.OC20241 cited

Output Feedback Control of Suspended Sediment Load Entrainment in Water Canals and Reservoirs

Eranda Somathilake, Mamadou Diagne

This paper addresses the management of water flow in a rectangular open channel, considering the dynamic nature of both the channel's bathymetry and the suspended sediment particle…

math.OC2024

Perfect Tracking of Time-Varying Optimum by Extremum Seeking

Cemal Tugrul Yilmaz, Mamadou Diagne, Miroslav Krstic

This paper introduces extremum seeking (ES) algorithms designed to achieve perfect tracking of arbitrary time-varying extremum. In contrast to classical ES approaches that employ c…

math.OC20232 cited

Exponential and Prescribed-Time Extremum Seeking with Unbiased Convergence

Cemal Tugrul Yilmaz, Mamadou Diagne, Miroslav Krstic

We present multivariable extremum seeking (ES) designs that achieve unbiased convergence to the optimum. Two designs are introduced: one with exponential unbiased convergence (unbi…

math.AP20239 cited

Deep Learning of Delay-Compensated Backstepping for Reaction-Diffusion PDEs

Shanshan Wang, Mamadou Diagne, Miroslav Krstić

Deep neural networks that approximate nonlinear function-to-function mappings, i.e., operators, which are called DeepONet, have been demonstrated in recent articles to be capable o…