29 citations · 39 across the 6 of their papers we have counts for
11 papers
Detection of Electric Motor Damage Through Analysis of Sound Signals Using Bayesian Neural Networks
Waldemar Bauer, Marta Zagorowska, Jerzy Baranowski
Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effec…
PI-CoF: A Bilevel Optimization Framework for Solving Active Learning Problems using Physics-Information
Liqiu Dong, Marta Zagorowska, Tong Liu +2
Physics informed neural networks (PINNs) have recently been proposed as surrogate models for solving process optimization problems. However, in an active learning setting collectin…
Degradation-aware data-enabled predictive control of energy hubs
Varsha Behrunani, Marta Zagorowska, Mathias Hudoba de Badyn +3
Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy…
Automatic scenario generation for efficient solution of robust optimal control problems
Marta Zagorowska, Paola Falugi, Edward O'Dwyer +1
Existing methods for nonlinear robust control often use scenario-based approaches to formulate the control problem as large nonlinear optimization problems. The optimization proble…
Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression
M. Zagorowska, M. Degner, L. Ortmann +4
Online Feedback Optimization is a method used to steer the operation of a process plant to its optimal operating point without explicitly solving a nonlinear constrained optimizati…
Efficient sample selection for safe learning
Marta Zagorowska, Efe C. Balta, Varsha Behrunani +2
Ensuring safety in industrial control systems usually involves imposing constraints at the design stage of the control algorithm. Enforcing constraints is challenging if the underl…
Safe Optimization of an Industrial Refrigeration Process Using an Adaptive and Explorative Framework
Buse Sibel Korkmaz, Marta Zagórowska, Mehmet Mercangöz
Many industrial applications rely on real-time optimization to improve key performance indicators. In the case of unknown process characteristics, real-time optimization becomes ch…
Fast and accurate method for computing non-smooth solutions to constrained control problems
Lucian Nita, Eduardo M. G. Vila, Marta A. Zagorowska +4
Introducing flexibility in the time-discretisation mesh can improve convergence and computational time when solving differential equations numerically, particularly when the soluti…
Automatic Scenario Generation for Robust Optimal Control Problems
Marta Zagorowska, Paola Falugi, Edward O'Dwyer +1
Existing methods for nonlinear robust control often use scenario-based approaches to formulate the control problem as nonlinear optimization problems. Increasing the number of scen…
Application of Gaussian Processes to online approximation of compressor maps for load-sharing in a compressor station
Akhil Ahmed, Marta Zagorowska, Ehecatl Antonio del Rio-Chanona +1
Devising optimal operating strategies for a compressor station relies on the knowledge of compressor characteristics. As the compressor characteristics change with time and use, it…
Data-driven predictive control with improved performance using segmented trajectories
Edward O'Dwyer, Eric C. Kerrigan, Paola Falugi +2
A class of data-driven control methods has recently emerged based on Willems' fundamental lemma. Such methods can ease the modelling burden in control design but can be sensitive t…