Searched for: subject%3A%22robustness%22
(41 - 60 of 456)

Pages

document
Tunca, Kerem (author)
This research has illustrated the abilities of incorporating robust decision making within train maintenance. Both scheduled and unscheduled maintenance processes of the Nederlandse Spoorwegen (NS) have been examined, after which exploratory modeling and analysis enabled developing valuable insights for decision makers. Scenario analysis through...
master thesis 2023
document
Sigurðsson, Snorri Þór (author)
Regular maintenance of civil engineering structures is essential for their safety. Current maintenance regimes involve periodic inspections at regular time intervals. In the time between inspections, there can be a critical development in the structural integrity of a structure, which can be expensive to repair or could even lead to structural...
master thesis 2023
document
Dong, Shawn (author)
This paper presents a train robust control method to optimize train operation based on the concept virtual coupling on train platoon. This approach is inspired by the recent development of platoon control for autonomous vehicles, and it is hoped that this platoon control can be applied to railway transportation. We use a decentralized model...
student report 2023
document
Wang, Yixia (author), Lin, Shu (author), Wang, Yibing (author), De Schutter, B.H.K. (author), Xu, Jungang (author)
Currently, with the development of driving technologies, driverless vehicles gradually are becoming more and more available. Therefore, there would be a long period of time during which self-driving vehicles and human-driven vehicles coexist. However, for a mixed platoon, it is hard to control the formation due to the existence of the manual...
journal article 2023
document
Reed, Robert (author), Laurenti, L. (author), Lahijanian, Morteza (author)
Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising tool to learn and control complex dynamical systems. In this letter, we develop a scalable abstraction-based framework that enables the use of DKL for control...
journal article 2023
document
Fransen, M.P. (author), Langelaar, Matthijs (author), Schott, D.L. (author)
In design optimization of bulk handling equipment (BHE) we generally focus on the mean performance of the equipment. However, granular materials behave stochastic due to irregularities in particle shape and size which leads to stochastic performance of the equipment. To include the stochastic performance we propose robust metamodel-based...
journal article 2023
document
Nazari-Shirkouhi, Salman (author), Miralizadeh Jalalat, Sepideh (author), Sangari, Mohamad Sadegh (author), Sepehri, A. (author), Rezaei Vandchali, Hadi (author)
Attaining sustainability objectives has received wide attention in the supplier selection and order allocation (SSOA) literature. This paper aims to investigate an SSOA problem under multiple items, multiple suppliers, multiple price levels, and multiple period using a robust-fuzzy multi-objective programming in which: (a) transportation cost,...
journal article 2023
document
Delissen, A.A.T.M. (author), van Keulen, A. (author), Langelaar, Matthijs (author)
The design of high-performance mechatronic systems is very challenging, as it requires delicate balancing of system dynamics, the controller, and their closed-loop interaction. Topology optimization provides an automated way to obtain systems with superior performance, although extension to simultaneous optimization of both topology and...
journal article 2023
document
Wang, Jiepeng (author), Zhou, Hong (author), Sun, Xinlei (author), Yuan, Y. (author)
Due to the fact that there is a lack of comprehensive understanding of how the dynamic nature of supply chain networks (SCNs) interrelates with network structures, particularly network topologies under disruptions. This research employs a novel evolving model of a supply chain network (SCNE model) by modifying the Barabási and Albert (BA)...
journal article 2023
document
Pourgholamali, Mohammadhosein (author), Correia, Gonçalo (author), Tarighati Tabesh, Mahmood (author), Esmaeilzadeh Seilabi, Sania (author), Miralinaghi, Mohammad (author), Labi, Samuel (author)
The rising demand for electric vehicles (EVs), motivated by their environmental benefits, is generating an increased need for EV charging infrastructure. Also, it has been recognized that the adequacy of such infrastructure helps promote EV use. Therefore, to facilitate EV adoption, governments seek guidance on continued investments in EV...
journal article 2023
document
Zisopoulos, Filippos K. (author), Noll, Dominik (author), Singh, Simron J. (author), Schraven, D.F.J. (author), de Jong, Martin (author), Fath, Brian D. (author), Goerner, Sally (author), Webster, Ken (author), Fiscus, Dan (author), Ulanowicz, Robert E. (author)
For many islands, the answer to the question “why a locally, self-sustaining, and regenerative economy is needed?” is clear. The struggle often lies in the “how”. Here, we argue that tools from regenerative economics, which follow an island economy-as-an-organism analogy, offer valuable and complementary insights to socio-metabolic research....
journal article 2023
document
Arnold, Wyatt (author), Zatarain Salazar, J. (author), Carlino, Angelo (author), Giuliani, Matteo (author), Castelletti, Andrea (author)
A resurgence of dam planning and construction is under way in river basins where untapped hydropower potential could meet growing energy demands. Despite calls for more comprehensive evaluation of dam projects, most dams continue to be planned with traditional methods that neglect interdependencies between planning and management and cumulative...
journal article 2023
document
Schwind, Nicolas (author), Demirović, E. (author), Inoue, Katsumi (author), Lagniez, Jean Marie (author)
In one of its simplest forms, Team Formation involves deploying the least expensive team of agents while covering a set of skills. While current algorithms are reasonably successful in computing the best teams, the resilience to change of such solutions remains an important concern: Once a team has been formed, some of the agents considered...
journal article 2023
document
Komini, Ludian (author), Langelaar, Matthijs (author), Kriegesmann, Benedikt (author)
This paper presents a method to consider uncertainties in the distortion prediction of additive manufacturing processes within robust topology optimization. The random variable of the stochastic additive manufacturing process is the inherent thermomechanical strain, typically determined by process characterization experiments. The value of...
journal article 2023
document
Guo, M. (author), De Persis, Claudio (author), Tesi, Pietro (author)
We consider data-driven control of input-affine systems via approximate nonlinearity cancellation. Data-dependent semi-definite program is developed to characterize the stabilizer such that the linear dynamics of the closed-loop systems is stabilized and the influence of the nonlinear dynamics is decreased. Because of the additional...
journal article 2023
document
Ghiassi, S. (author), Birke, Robert (author), Chen, Lydia Y. (author)
Learning robust deep models against noisy labels becomes ever critical when today's data is commonly collected from open platforms and subject to adversarial corruption. The information on the label corruption process, i.e., corruption matrix, can greatly enhance the robustness of deep models but still fall behind in combating hard classes....
conference paper 2023
document
Nguyen, Viet Anh (author), Shafieezadeh-Abadeh, Soroosh (author), Kuhn, Daniel (author), Mohajerin Esfahani, P. (author)
We introduce a distributionally robust minimium mean square error estimation model with a Wasserstein ambiguity set to recover an unknown signal from a noisy observation. The proposed model can be viewed as a zero-sum game between a statistician choosing an estimator—that is, a measurable function of the observation—and a fictitious adversary...
journal article 2023
document
Lengyel, A. (author), Strafforello, O. (author), Bruintjes, R. (author), Gielisse, A.S. (author), van Gemert, J.C. (author)
Color is a crucial visual cue readily exploited by Convolutional Neural Networks (CNNs) for object recognition. However, CNNs struggle if there is data imbalance between color variations introduced by accidental recording conditions. Color invariance addresses this issue but does so at the cost of removing all color information, which sacrifices...
conference paper 2023
document
Tacx, Paul (author), Oomen, T.A.E. (author)
The selection of uncertainty structures is an important aspect of system identification for robust control. The aim of this paper is to provide insight into uncertain multivariable systems for robust control. A unified method for visualizing model sets is developed by generating Bode plots of multivariable uncertain systems, both in magnitude...
journal article 2023
document
Seilabi, Sania E. (author), Pourgholamali, Mohammadhosein (author), Correia, Gonçalo (author), Labi, Samuel (author)
Reduced headways of connected and automated vehicles (CAV) provide opportunities to address traffic congestion and environmental adversities. This benefit can be utilized by deploying CAV-dedicated lanes (CAVDL). This paper presents a bi-level optimization model that captures CAV market size uncertainty. The upper level determines the links ...
journal article 2023
Searched for: subject%3A%22robustness%22
(41 - 60 of 456)

Pages