3 papers
math.OC2024
QP Based Constrained Optimization for Reliable PINN Training
Alan Williams, Christopher Leon, Alexander Scheinker
Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for integrating physics-based constraints and data to address forward and inverse problems in machine learn…
math.OC2024
Practical Safe Extremum Seeking with Assignable Rate of Attractivity to the Safe Set
Alan Williams, Miroslav Krstic, Alexander Scheinker
We present Assignably Safe Extremum Seeking (ASfES), an algorithm designed to minimize a measured objective function while maintaining a measured metric of safety (a control barrie…
math.OC2023
Semi-Global Practical Extremum Seeking with Practical Safety
Alan Williams, Miroslav Krstic, Alexander Scheinker
We introduce a type of safe extremum seeking (ES) controller, which minimizes an unknown objective function while also maintaining practical positivity of an unknown barrier functi…