High Orders Computational Techniques Applied to Space Dynamics

  • Mohammad Alhulayil

Student thesis: Doctoral Thesis


Mohammad Alhulayil, High Orders Computational Techniques Applied to Space Dynamics', PhD. Thesis, PhD in Engineering, Department of Electrical and Computer Engineering, Khalifa University of Science and Technology, United Arab Emirates. Many applications in science and engineering require the calculations of partial derivative models. The main objective of this dissertation is to develop and demonstrate new computational methods for estimation and optimization of dynamical systems that use Automatic Differentiation (AD). The main focus of this dissertation will be on dynamical systems of Aerospace Engineering. Computational Differentiation (CD) is a specialized topic in applied mathematics and computer science for developing software tools for numerically evaluating partial derivative models. The computational differentiation tool that is used through this work will be the OCEA (Object-oriented Coordinate Embedded Algorithm). OCEA is a suite of programs that transform user supplied software math models, with minimal modifications, for generating high-order sensitivity models. The core of this dissertation details the efficient use of OCEA through some computational techniques applied in space dynamics. Some of the common problems in space dynamics are studied ranging from Lambert's problem, Satellite attitude estimation, and orbit determination of Satellite motion. New solutions for these problems are introduced by using higher order models based on OCEA to prove the ability of this computational differentiation tool to improve the speed of convergence and the domain of convergence while preserving the computation accuracy and the computation cost. The memory limitations tradeoffs resulting from applying higher order models in these problems are studied by exploiting the symmetry and sparsity aspects in the higher order tensor based applications to keep the memory managed during the generation, storage and computation of higher order sensitivity models.
Date of AwardMay 2018
Original languageAmerican English
SupervisorAhmad Younes (Supervisor)


  • Computational Techniques; Space Dynamics; Automatic Differentiation; Computational Differentiation; OCEA.

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