44 citations · 250 across the 61 of their papers we have counts for
10 papers · 1 filter
Dampening parameter distributional shifts under robust control and gain scheduling
Mohammad Ramadan, Mihai Anitescu
Many traditional robust control approaches assume linearity of the system and independence between the system state-input and the parameters of its approximant (possibly lower-orde…
Improved Approximation Bounds for Moore-Penrose Inverses of Banded Matrices with Applications to Continuous-Time Linear Quadratic Control
Sungho Shin, Wallace Gian Yion Tan, Mihai Anitescu
We present improved approximation bounds for the Moore-Penrose inverses of banded matrices, where the bandedness is induced by a metric on the index set. We show that the pseudoinv…
Data-conforming data-driven control: avoiding premature generalizations beyond data
Mohammad Ramadan, Evan Toler, Mihai Anitescu
Data-driven and adaptive control approaches face the problem of introducing sudden distributional shifts beyond the distribution of data encountered during learning. Therefore, the…
The statistical spread of transmission outages on a fast protection time scale based on utility data
Ian Dobson, D. Adrian Maldonado, Mihai Anitescu
When there is a fault, the protection system automatically removes one or more transmission lines on a fast time scale of less than one minute. The outaged lines form a pattern in…
A Framework for Balancing Power Grid Efficiency and Risk with Bi-objective Stochastic Integer Optimization
Ramsey Rossmann, Mihai Anitescu, Julie Bessac +4
Power grid expansion planning requires making large investment decisions in the present that will impact the future cost and reliability of a system exposed to wide-ranging uncerta…
Scalable Multi-Period AC Optimal Power Flow Utilizing GPUs with High Memory Capacities
Sungho Shin, Vishwas Rao, Michel Schanen +2
This paper demonstrates the scalability of open-source GPU-accelerated nonlinear programming (NLP) frameworks -- ExaModels.jl and MadNLP.jl -- for solving multi-period alternating…
Condensed Interior-Point Methods for Scalable Nonlinear Programming on GPUs
François Pacaud, Sungho Shin, Alexis Montoison +2
This paper explores two variants of condensed-space interior-point methods designed for GPUs - HyKKT and LiftedKKT - by analyzing their numerical properties through error analysis…
Extended Kalman filter -- Koopman operator for tractable stochastic optimal control
Mohammad S. Ramadan, Mihai Anitescu
The theory of dual control was introduced more than seven decades ago. Although it has provided rich insights to the fields of control, estimation, and system identification, dual…
Parallel Sequential Quadratic Programming with Overlapping Graph Decomposition and Exact Augmented Lagrangian
Runxin Ni, Haoxuan Wang, Sen Na +2
In this paper, we address the challenge of solving large-scale graph-structured nonlinear programs (gsNLPs) in a scalable manner. GsNLPs are problems in which the objective and con…
Data-Driven Estimation of Failure Probabilities in Correlated Structure-Preserving Stochastic Power System Models
Hongli Zhao, Tyler E. Maltba, D. Adrian Maldonado +2
We propose a data-driven approach for propagating uncertainty in stochastic power grid simulations and apply it to the estimation of transmission line failure probabilities. A redu…