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Model instability and poor prediction of long-term behavior are common problems when modeling dynamical systems using nonlinear "black-box" techniques. Direct optimization of the long-term predictions, often called simulation error…

Systems and Control · Computer Science 2017-01-25 Mark M. Tobenkin , Ian R. Manchester , Alexandre Megretski

In this work we consider the generalized Navier-Stoke equations with the presence of a damping term in the momentum equation. % The problem studied here derives from the set of equations which govern the isothermal flow of incompressible,…

Analysis of PDEs · Mathematics 2011-09-27 Hermenegildo Borges de Oliveira

The decarbonization of many heavy power-consuming industries is dependent on the integration of renewable energy sources and energy storage systems in isolated autonomous power systems. The optimal energy management in such schemes becomes…

Systems and Control · Electrical Eng. & Systems 2022-08-19 Spyridon Chapaloglou , Erick Alves , Vincenzo Trovato , Elisabetta Tedeschi

Accurate knowledge of natural gas network topology is critical for the proper operation of natural gas networks. Failures, physical attacks, and cyber attacks can cause the actual natural gas network topology to differ from what the…

Signal Processing · Electrical Eng. & Systems 2020-04-03 Zisheng Wang , Rick S. Blum

In this work we analyse a stochastic control problem for the valuation of a natural gas power station while taking into account operating characteristics. Both electricity and gas spot price processes exhibit mean-reverting spikes and…

Mathematical Finance · Quantitative Finance 2016-08-02 Nemat Safarov , Colin Atkinson

Wind generation is traditionally treated as a non-dispatchable resource and is fully absorbed unless there are security issues. To tackle the operational reliability issues caused by the volatile and non-dispatchable wind generation, many…

Optimization and Control · Mathematics 2015-11-13 Cheng Wang , Feng Liu , Feng Qiu , Wei Wei , Jianhui Wang , Shengwei Mei

A novel robust nonlinear model predictive control strategy is proposed for systems with nonlinear dynamics and convex state and control constraints. Using a sequential convex approximation approach and a difference of convex functions…

Optimization and Control · Mathematics 2025-01-28 Yana Lishkova , Mark Cannon

A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical…

Systems and Control · Electrical Eng. & Systems 2022-02-18 Jiaxu Li , Yin Xu , Ying Wang , Meng Li , Jinghan He , Chen-Ching Liu , Kevin P. Schneider

The construction of a cost minimal network for flows obeying physical laws is an important problem for the design of electricity, water, hydrogen, and natural gas infrastructures. We formulate this problem as a mixed-integer non-linear…

Optimization and Control · Mathematics 2025-03-31 Pascal Börner , Max Klimm , Annette Lutz , Marc E. Pfetsch , Martin Skutella , Lea Strubberg

Gas networks are used to transport natural gas, which is an important resource for both residential and industrial customers throughout the world. The gas network design problem is generally modelled as a nonconvex mixed-integer nonlinear…

Optimization and Control · Mathematics 2024-02-01 Yijiang Li , Santanu S. Dey , Nikolaos V. Sahinidis

Within the current sphere of deep learning research, despite the extensive application of optimization algorithms such as Stochastic Gradient Descent (SGD) and Adaptive Moment Estimation (Adam), there remains a pronounced inadequacy in…

Machine Learning · Computer Science 2025-10-30 Zhifeng Wang , Longlong Li , Chunyan Zeng

We develop the theory of Energy Conserving Descent (ECD) and introduce ECDSep, a gradient-based optimization algorithm able to tackle convex and non-convex optimization problems. The method is based on the novel ECD framework of…

Machine Learning · Computer Science 2023-06-02 G. Bruno De Luca , Alice Gatti , Eva Silverstein

Efficient analysis and simulation of multiscale stochastic systems of chemical kinetics is an ongoing area for research, and is the source of many theoretical and computational challenges. In this paper, we present a significant improvement…

Numerical Analysis · Mathematics 2016-09-21 Simon Cotter

Liquefied Natural Gas (LNG) transportation is a critical component of the energy industry. It enables the efficient and large-scale movement of natural gas across vast distances by converting it into a liquid form, thereby addressing global…

Optimization and Control · Mathematics 2025-11-12 S. Iudin , M. Veshchezerova , K. Tsarova , G. Tadumadze , V. Shete , J. -K. Hao , M. Perelshtein

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

In this Series, we study the weakly nonlinear dynamics of chemically active particles near the threshold for spontaneous motion. In this part, we focus on steady solutions and develop an `adjoint method' for deriving the nonlinear amplitude…

Fluid Dynamics · Physics 2022-11-18 Ory Schnitzer

This paper proposes novel gradient-flow schemes that yield convergence to the optimal point of a convex optimization problem within a \textit{fixed} time from any given initial condition for unconstrained optimization, constrained…

Optimization and Control · Mathematics 2022-04-27 Kunal Garg , Dimitra Panagou

The critical role of gas fired-plants to compensate renewable generation has increased the operational variability in natural gas networks (GN). Towards developing more reliable and efficient computational tools for GN monitoring, control,…

Optimization and Control · Mathematics 2018-09-25 Manish K. Singh , Vassilis Kekatos

Fractures are normally present in the underground and are, for some physical processes, of paramount importance. Their accurate description is fundamental to obtain reliable numerical outcomes useful, e.g., for energy management. Depending…

Numerical Analysis · Mathematics 2021-03-03 Alessio Fumagalli , Francesco Saverio Patacchini

Optimization problems with rank constraints appear in many diverse fields such as control, machine learning and image analysis. Since the rank constraint is non-convex, these problems are often approximately solved via convex relaxations.…

Optimization and Control · Mathematics 2018-11-12 Christian Grussler , Pontus Giselsson
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