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This paper proposes a robust version of the unscented transform (UT) for one-dimensional random variables. It is assumed that the moments are not exactly known, but are known to lie in intervals. In this scenario, the moment matching…

Statistics Theory · Mathematics 2019-02-26 Hugo T. M. Kussaba , João Y. Ishihara , Leonardo R. A. X. Menezes

The purpose of this paper is to examine the Lagrangian stochastic modeling of the fluid velocity seen by inertial particles in a nonhomogeneous turbulent flow. A new Langevin-type model, compatible with the transport equation of the drift…

Fluid Dynamics · Physics 2009-07-01 Boris Arcen , Anne Tanière

This paper investigates the application of zonotope-based reachability analysis to low-thrust spacecraft in both two-body and cislunar environments. Reachable sets are generated under two-body and circular restricted three-body (CR3BP)…

Systems and Control · Electrical Eng. & Systems 2026-01-27 Jinaykumar Patel , Kamesh Subbarao

With the increasing penetration of Inverter-Based Resources (IBRs) and their impact on power system stability and operation, the concept of stability-constrained optimization has drawn significant attention from researchers. In order to…

Systems and Control · Electrical Eng. & Systems 2024-04-23 Zhongda Chu , Fei Teng

This study addresses optimal impulsive trajectory design within the Circular Restricted Three-Body Problem (CR3BP), presenting a global optimization-based approach to identify minimum $\Delta V$ transfers between periodic orbits, including…

Space Physics · Physics 2024-05-30 Flavio Tagliaferri , Emmanuel Blazquez , Giacomo Acciarini , Dario Izzo

In highly nonlinear systems such as the ones commonly found in astrodynamics, Gaussian distributions generally evolve into non-Gaussian distributions. This paper introduces a method for effectively controlling non-Gaussian distributions in…

Systems and Control · Electrical Eng. & Systems 2025-10-16 Daniel C. Qi , Kenshiro Oguri , Puneet Singla , Maruthi R. Akella

In this article we study the problem of quantifying the uncertainty in an experiment with a technical system. We propose new density estimates which combine observed data of the technical system and simulated data from an (imperfect)…

Statistics Theory · Mathematics 2020-12-21 Sebastian Kersting , Michael Kohler

The goal of this presentation is to highlight various computational techniques used to study dynamics of quantum many-body systems. We examine the projection and variable phase methods being applied to multi-channel problems of scattering…

Nuclear Theory · Physics 2014-12-22 Alexander Volya

Complex engineering systems require integration of simulation of sub-systems and calculation of metrics to drive design decisions. This paper introduces a methodology for designing computational or physical experiments for system-level…

Computational Engineering, Finance, and Science · Computer Science 2024-05-24 Efe Y. Yarbasi , Dimitri N. Mavris

The case of the planar circular restricted three-body problem is used as a test field in order to determine the character of the orbits of a small body which moves under the gravitational influence of the two heavy primary bodies. We…

Space Physics · Physics 2017-09-28 Euaggelos E. Zotos

The investigation of the nonequilibrium quantum dynamics of bosonic many-body systems is very challenging due to the excessively growing Hilbert space and poses a major problem for their theoretical description and simulation. We present a…

Quantum Gases · Physics 2019-08-07 F. Köhler , K. Keiler , S. I. Mistakidis , H. -D. Meyer , P. Schmelcher

The paper algorithmizes the problem of regime change point identification for data measured in a system exhibiting impulsive behaviors. This is a fundamental challenge for annotation of measurement data relevant, e.g., for designing…

This paper presents a probabilistic approach to represent and quantify model-form uncertainties in the reduced-order modeling of complex systems using operator inference techniques. Such uncertainties can arise in the selection of an…

Machine Learning · Statistics 2024-11-08 Jin Yi Yong , Rudy Geelen , Johann Guilleminot

This paper considers the problem of steering the state distribution of a nonlinear stochastic system from an initial Gaussian to a terminal distribution with a specified mean and covariance, subject to probabilistic path constraints. An…

Optimization and Control · Mathematics 2019-09-16 Jack Ridderhof , Kazuhide Okamoto , Panagiotis Tsiotras

Particle number fluctuations $N(t)$, measured in virtual observation boxes of an image or a simulation, offer a way to quantify particle dynamics when particle tracking is impractical, such as in high-density systems. While traditionally…

Soft Condensed Matter · Physics 2026-04-07 Tristan Cerdin , Talia Calazans , Carine Douarche , Sophie Marbach

Designing robust space trajectories in nonlinear dynamical environments, such as the Earth-Moon circular restricted three-body problem (CR3BP), poses significant challenges due to sensitivity to initial conditions and non-Gaussian…

Optimization and Control · Mathematics 2026-05-13 Thomas Caleb , Roberto Armellin , Stéphanie Lizy-Destrez

This work utilizes a particle swarm optimizer (PSO) for initial orbit determination for a chief and deputy scenario in the circular restricted three-body problem (CR3BP). The PSO is used to minimize the difference between actual and…

Uncertainty modeling has become increasingly important in power system decision-making. The widely-used tractable uncertainty modeling method-chance constraints with Conditional Value at Risk (CVaR) approximation, can be overconservative…

Optimization and Control · Mathematics 2024-07-02 Yilin Wen , Yi Guo , Zechun Hu , Gabriela Hug

The unscented transformation (UT) is an efficient method to solve the state estimation problem for a non-linear dynamic system, utilizing a derivative-free higher-order approximation by approximating a Gaussian distribution rather than…

Machine Learning · Statistics 2016-08-29 Xi Liu , Badong Chen , Bin Xu , Zongze Wu , Paul Honeine

Standard chance constrained control algorithms typically rely on the assumption that uncertainties in vehicle states obey Gaussian statistics. Highly nonlinear systems tend to disrupt Gaussianity, challenging standard chance-constrained…

Optimization and Control · Mathematics 2026-04-07 Ethan Burnett , Spencer Boone