Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Zagorowska, Marta A."'
Ensuring safety is a key aspect in sequential decision making problems, such as robotics or process control. The complexity of the underlying systems often makes finding the optimal decision challenging, especially when the safety-critical system is
Externí odkaz:
http://arxiv.org/abs/2409.18000
Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effective and reliable classifiers for diagnostics of equipment is challeng
Externí odkaz:
http://arxiv.org/abs/2409.08309
Physics informed neural networks (PINNs) have recently been proposed as surrogate models for solving process optimization problems. However, in an active learning setting collecting enough data for reliably training PINNs poses a challenge. This stud
Externí odkaz:
http://arxiv.org/abs/2402.13588
Online Feedback Optimization (OFO) controllers steer a system to its optimal operating point by treating optimization algorithms as auxiliary dynamic systems. Implementation of OFO controllers requires setting the parameters of the optimization algor
Externí odkaz:
http://arxiv.org/abs/2312.01996
Autor:
Zagorowska, Marta, König, Christopher, Yu, Hanlin, Balta, Efe C., Rupenyan, Alisa, Lygeros, John
Optimization-based controller tuning is challenging because it requires formulating optimization problems explicitly as functions of controller parameters. Safe learning algorithms overcome the challenge by creating surrogate models from measured dat
Externí odkaz:
http://arxiv.org/abs/2310.17431
Autor:
Behrunani, Varsha, Zagorowska, Marta, de Badyn, Mathias Hudoba, Ricca, Francesco, Heer, Philipp, Lygeros, John
Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a building, whil
Externí odkaz:
http://arxiv.org/abs/2307.01543
Existing methods for nonlinear robust control often use scenario-based approaches to formulate the control problem as large nonlinear optimization problems. The optimization problems are challenging to solve due to their size, especially if the contr
Externí odkaz:
http://arxiv.org/abs/2303.08540
Ensuring safety in industrial control systems usually involves imposing constraints at the design stage of the control algorithm. Enforcing constraints is challenging if the underlying functional form is unknown. The challenge can be addressed by usi
Externí odkaz:
http://arxiv.org/abs/2211.14104
Safe Optimization of an Industrial Refrigeration Process Using an Adaptive and Explorative Framework
Many industrial applications rely on real-time optimization to improve key performance indicators. In the case of unknown process characteristics, real-time optimization becomes challenging, particularly for the satisfaction of safety constraints. In
Externí odkaz:
http://arxiv.org/abs/2211.13019
We consider the problem of decision-making under uncertainty in an environment with safety constraints. Many business and industrial applications rely on real-time optimization to improve key performance indicators. In the case of unknown characteris
Externí odkaz:
http://arxiv.org/abs/2211.05495