Alberto Fossà

ORCID: 0000-0002-0756-4998
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About
Contact & Profiles
Research Areas
  • Fault Detection and Control Systems
  • Target Tracking and Data Fusion in Sensor Networks
  • Spacecraft Dynamics and Control
  • Astro and Planetary Science
  • Stellar, planetary, and galactic studies
  • Inertial Sensor and Navigation
  • Quantum chaos and dynamical systems
  • Probabilistic and Robust Engineering Design
  • Space Satellite Systems and Control
  • Matrix Theory and Algorithms
  • Control Systems and Identification
  • Planetary Science and Exploration
  • Analytical Chemistry and Chromatography
  • Image Processing Techniques and Applications
  • Nuclear reactor physics and engineering
  • Numerical methods for differential equations

Institut Superieur de l'Aeronautique et de l'Espace (ISAE-SUPAERO)
2020-2024

University of Auckland
2023-2024

University of Padua
2020

This paper introduces a novel method for the automatic detection and handling of nonlinearities in generic transformation. A nonlinearity index that exploits second-order Taylor expansions polynomial bounding techniques is first introduced to estimate Jacobian variation nonlinear then embedded into low-order domain splitting algorithm accurately describes mapping an initial uncertainty set through transformation by whenever grow above predefined threshold. The illustrated critical case...

10.2514/1.g007271 article EN Journal of Guidance Control and Dynamics 2024-01-18

View Video Presentation: https://doi.org/10.2514/6.2022-0859.vid A new multifidelity method is developed for nonlinear orbit uncertainty propagation. This approach guarantees improved computational efficiency and limited accuracy losses compared with fully high-fidelity counterparts. The initial modeled as a weighted sum of Gaussian distributions whose number adapted online to satisfy the required accuracy. As needed, univariate splitting libraries are used split mixture components along...

10.2514/6.2022-0859 article EN AIAA SCITECH 2022 Forum 2022-01-03

A multifidelity method for the nonlinear propagation of uncertainties in presence stochastic accelerations is presented. The proposed algorithm treats uncertainty (UP) problem by separating initial from that process noise. propagated using an adaptive Gaussian mixture model (GMM) which exploits a low-fidelity dynamical to minimize computational costs. effects noise are instead computed PoLynomial Algebra Stochastic Moments Analysis (PLASMA) technique, considers high-fidelity dynamics. main...

10.48550/arxiv.2405.15993 preprint EN arXiv (Cornell University) 2024-05-24

A new multifidelity method is developed for nonlinear orbit uncertainty propagation. This approach guarantees improved computational efficiency and limited accuracy losses compared to fully high-fidelity counterparts. The initial modeled as a weighted sum of Gaussian distributions whose number adapted online satisfy the required accuracy. As needed, univariate splitting libraries are used split mixture components along direction maximum nonlinearity. Differential Algebraic techniques...

10.48550/arxiv.2203.15559 preprint EN cc-by-nc-nd arXiv (Cornell University) 2022-01-01

This paper presents an algorithm for the preprocessing of observation data aimed at improving robustness orbit determination tools. Two objectives are fulfilled: obtain a refined solution to initial problem and detect possible outliers in processed measurements. The uncertainty on estimate is propagated forward time progressively reduced by exploiting sensor available said propagation window. Differential algebra techniques novel automatic domain splitting second-order Taylor expansions used...

10.48550/arxiv.2302.14655 preprint EN cc-by-nc-nd arXiv (Cornell University) 2023-01-01

This paper introduces a novel method for the automatic detection and handling of nonlinearities in generic transformation. A nonlinearity index that exploits second order Taylor expansions polynomial bounding techniques is first introduced to rigorously estimate Jacobian variation nonlinear then embedded into low-order domain splitting algorithm accurately describes mapping an initial uncertainty set through transformation by whenever some imposed linearity constraints are non met. The...

10.48550/arxiv.2303.05791 preprint EN cc-by-nc-nd arXiv (Cornell University) 2023-01-01

An algorithm for robust initial orbit determination (IOD) under perturbed orbital dynamics is presented. By leveraging map inversion techniques defined in the algebra of Taylor polynomials, this tool returns a highly accurate solution to IOD problem and estimates range centered on aforementioned which true should lie. To meet specified accuracy requirements, automatic domain splitting used wrap routines ensure that local truncation error, introduced by polynomial representation state...

10.48550/arxiv.2306.09699 preprint EN cc-by-nc-nd arXiv (Cornell University) 2023-01-01

Abstract The return of human space missions to the Moon puts Earth-Moon system (EMS) at center attention. Hence, studying periodic solutions circular restricted three-body problem (CR3BP) is crucial ease transfer computations, find new solutions, or better understand these orbits. This work proposes a novel continuation method families using differential algebra (DA) mapping. We exploit DA with automatic control truncation error represent each family orbits as set 2D Taylor polynomial maps....

10.21203/rs.3.rs-2024872/v1 preprint EN cc-by Research Square (Research Square) 2022-09-29
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