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Abolfazl Shirazi

Ph.D Fellow


I am a Ph.D student at University of the Basque Country (Universidad del País Vasco), Spain. My field of study is Computer Science and I am so passionate about Astrodynamics and Orbital Mechanics. I received my B.Sc and M.Sc degrees in Aerospace Engineering and in my Ph.D program, I work on the the development of Machine Learning techniques for spacecraft trajectory optimization problems. I have been awarded the La Caixa fellowship in 2016 and joined the Machine Learning Group at Basque Center for Applied Mathematics (BCAM) as a Ph.D student.


Researches


Orbital Mechanics

Orbit Propagation
Orbital Maneuvers
Trajectory Optimization
Interplanetary Transfers

Machine Learning

Metaheuristics
Continuous Optimization
Evolutionary Algorithms
Clustering

Spacecraft Dynamics

Spacecraft Guidance
Satellite Attitude Control
Space Mission Analysis
G.N.C Systems

3D
Simulation

3D Visualization
Software Development
3D Design & Modeling
Realtime Simulation

Featured Articles


An evolutionary discretized Lambert approach for optimal long-range rendezvous considering impulse limit
Shirazi, A., Ceberio, J. and Lozano, J.A.
Aerospace Science and Technology 94 (2019): 105400
DOI: 10.1016/j.ast.2019.105400
Abstract:
In this paper, an approach is presented for finding the optimal long-range space rendezvous in terms of fuel and time, considering limited impulse. In this approach, the Lambert problem is expanded towards a discretized multi-impulse transfer. Taking advantage of an analytical form of multi-impulse transfer, a feasible solution that satisfies the impulse limit is calculated. Next, the obtained feasible solution is utilized as a seed for generating individuals for a hybrid self-adaptive evolutionary algorithm to minimize the total time, without violating the impulse limit while keeping the overall fuel mass the same as or less than the one associated with the analytical solution. The algorithm eliminates similar individuals and regenerates them based on a combination of Gaussian and uniform distribution of solutions from the fuel-optimal region during the optimization process. Other enhancements are also applied to the algorithm to make it auto-tuned and robust to the initial and final orbits as well as the impulse limit. Several types of the proposed algorithm are tested considering varieties of rendezvous missions. Results reveal that the approach can successfully reduce the overall transfer time in the multi-impulse transfers while minimizing the fuel mass without violating the impulse limit. Furthermore, the proposed algorithm has superior performance over standard evolutionary algorithms in terms of convergence and optimality.

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions
Shirazi, A., Ceberio, J. and Lozano, J.A.
Progress in Aerospace Sciences 102 (2018): 76-98
DOI: 10.1016/j.paerosci.2018.07.007
Abstract:
This article is a survey paper on solving spacecraft trajectory optimization problems. The solving process is decomposed into four key steps of mathematical modeling of the problem, defining the objective functions, development of an approach and obtaining the solution of the problem. Several subcategories for each step have been identified and described. Subsequently, important classifications and their characteristics have been discussed for solving the problems. Finally, a discussion on how to choose an element of each step for a given problem is provided.


E-mail:
  • ashirazi@bcamath.org
  • ashirazi@homasim.com
Contact:
  • Tel: +34 946 567 842
  • Fax: +34 946 567 843
Address:
    Mazarredo, 14, 48009
    Bilbao, Spain
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