M. Amin Alandihallaj

ORCID: 0000-0002-8526-3605
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About
Contact & Profiles
Research Areas
  • Spacecraft Design and Technology
  • Satellite Communication Systems
  • Spacecraft Dynamics and Control
  • Space Satellite Systems and Control
  • Astro and Planetary Science
  • Inertial Sensor and Navigation
  • Spacecraft and Cryogenic Technologies
  • Microgrid Control and Optimization
  • Reliability and Maintenance Optimization
  • Software Reliability and Analysis Research
  • Adaptive Control of Nonlinear Systems
  • Planetary Science and Exploration
  • Age of Information Optimization
  • Distributed and Parallel Computing Systems
  • Fault Detection and Control Systems
  • Magnetic Bearings and Levitation Dynamics
  • Aerospace Engineering and Control Systems
  • Optimization and Search Problems
  • Radiation Effects in Electronics
  • Wave and Wind Energy Systems
  • Rocket and propulsion systems research
  • Underwater Vehicles and Communication Systems
  • Space exploration and regulation

University of Luxembourg
2023-2024

University of Toronto
2021-2022

During orbital rendezvous, the spacecraft typically approach in same plane, and phase of orbit eventually aligns. Potential rendezvous docking missions need to be emulated tested an on-ground facility for micro-gravity research prior meeting harsh conditions space environment. For docking, velocity profile two must matched. The chaser is placed a slightly lower than target. Since all these tasks are quite complex realization very expensive, any space-related hardware or software's...

10.1016/j.jsse.2023.09.003 article EN cc-by Journal of Space Safety Engineering 2023-10-06

The increasing deployment of CubeSats in space missions necessitates the development efficient and reliable orbital maneuvering techniques, particularly given constraints on fuel capacity computational resources. This paper presents a novel two-level control architecture designed to enhance accuracy robustness CubeSat maneuvers. proposed method integrates -optimized sequence at high level leverage natural perturbative effects for fuel-efficient orbit corrections, with gated recurrent unit...

10.3390/aerospace11100807 article EN cc-by Aerospace 2024-09-30

The objective of this paper is to provide a stochastic framework optimally avoid collision between maneuverable spacecraft and space object or debris. satellite can be caused through cyber-attack on by colliding it with considered strategic satellite. Consequently, highly imperative that critical operational assets provided autonomous avoidance systems. methodology proposed in will reduce the probability an acceptable level protect against indirect kinetic cyber-attacks initiated designing...

10.1080/00207179.2022.2078423 article EN International Journal of Control 2022-05-14

In the field of space exploration, floating platforms play a crucial role in scientific investigations and technological advancements. However, controlling these zero-gravity environments presents unique challenges, including uncertainties disturbances. This paper introduces an innovative approach that combines Proximal Policy Optimization (PPO) with Model Predictive Control (MPC) laboratory (Zero-G Lab) at University Luxembourg. leverages PPO's reinforcement learning power MPC's precision...

10.48550/arxiv.2407.03224 preprint EN arXiv (Cornell University) 2024-07-03

CubeSats offer a cost-effective platform for various space missions, but their limited fuel capacity and susceptibility to environmental disturbances pose significant challenges precise orbital maneuvering. This paper presents novel control strategy that integrates J2-optimized sequence with an LSTM-based low-level layer address these issues. The leverages the Earth's oblateness minimize consumption during corrections, while LSTM network provides real-time adjustments compensate external...

10.48550/arxiv.2410.10240 preprint EN arXiv (Cornell University) 2024-10-14

This paper presents a Hierarchical Reinforcement Learning methodology tailored for optimizing CubeSat task scheduling in Low Earth Orbits (LEO). Incorporating high-level policy global distribution and low-level real-time adaptations as safety mechanism, our approach integrates the Similarity Attention-based Encoder (SABE) prioritization an MLP estimator energy consumption forecasting. Integrating this mechanism creates safe fault-tolerant system scheduling. Simulation results validate...

10.48550/arxiv.2309.12004 preprint EN cc-by arXiv (Cornell University) 2023-01-01

This methods paper outlines the development of Zero-G Laboratory at University Luxembourg, a crucial resource for advancing research in space operations. The primary objective this laboratory is to meticulously simulate micro-gravity conditions encountered space, allowing comprehensive testing space-related hardware and software before their deployment demanding environment outer space. key employed establishing facility include replicating space-representative infrastructure elements such...

10.2139/ssrn.4602588 preprint EN 2023-01-01
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