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20242026
most citedMesh Refinement with Early Termination for Dynamic Feasibility Problems

1 citations · 2 across the 15 of their papers we have counts for

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math.OC2026

Direct Inference on Admissible Sets (Diona)

Lorenzo Sabug, Eric Kerrigan

We propose a new regression method named Direct Inference on Admissible Sets (Diona) that directly uses samples to estimate the state and its derivatives at a query point, along wi…

math.OC2026

Generalized Semi-Infinite Programming for Robust Optimal Control with Decision-Dependent Uncertainty

J. Wehbeh, E. C. Kerrigan, E. Scaccia

Generalized semi-infinite programs (GSIPs) arise in robust optimal control whenever the admissible uncertainty depends on the state or controls. Existing GSIP methods either impose…

math.OC2026

An Efficient Method for the Optimal Control of Microgrids Under Uncertainties using Local Reduction

Edoardo Scaccia, Eric C. Kerrigan, Anna Sadowska

The problem of optimal sizing and power scheduling in microgrids subject to uncertainties is well known to the control community. Commonly, the optimal control problem is cast as a…

math.OC2026

A New Duality-Free Framework for Convex Optimisation with Superlinear Convergence and Effective Warm-Starting

Michael Cummins, Eric Kerrigan

Modern second order solvers for convex optimisation, such as interior point methods, rely on primal dual information and are difficult to warm start, limiting their applicability i…

math.OC2025

Rethinking Physics-Informed Regression Beyond Training Loops and Bespoke Architectures

Lorenzo Sabug, Eric Kerrigan

We revisit the problem of physics-informed regression, and propose a method that directly computes the state at the prediction point, simultaneously with the derivative and curvatu…

math.OC2025

State-Dependent Uncertainty Modeling in Robust Optimal Control Problems through Generalized Semi-Infinite Programming

J. Wehbeh, E. C. Kerrigan

Generalized semi-infinite programs (generalized SIPs) are problems featuring a finite number of decision variables but an infinite number of constraints. They differ from standard…

math.OC2024

Semi-Infinite Programs for Robust Control and Optimization: Efficient Solutions and Extensions to Existence Constraints

Jad Wehbeh, Eric C. Kerrigan

Discrete-time robust optimal control problems generally take a min-max structure over continuous variable spaces, which can be difficult to solve in practice. In this paper, we ext…

math.OC2024★ 1 cited

Mesh Refinement with Early Termination for Dynamic Feasibility Problems

Eduardo M. G. Vila, Eric C. Kerrigan, Paul Bruce

We propose a novel early-terminating mesh refinement strategy using an integrated residual method to solve dynamic feasibility problems. As a generalization of direct collocation,…

math.OC2024

Tight Bounds on Polynomials and Its Application to Dynamic Optimization Problems

Eduardo M. G. Vila, Eric C. Kerrigan, Paul Bruce

This paper presents a pseudo-spectral method for Dynamic Optimization Problems (DOPs) that allows for tight polynomial bounds to be achieved via flexible sub-intervals. The propose…