Projective Transformations for Regularized Central-Force Dynamics: Hamiltonian Formulation
Joseph T.A. Peterson, Manoranjan Majji, and John L. Junkins

TL;DR
This paper develops a Hamiltonian-based regularization method for central-force dynamics using projective transformations, enabling simplified solutions and numerical validation for perturbed two-body problems.
Contribution
It introduces a novel canonical extension of projective decomposition within Hamiltonian dynamics for regularizing and linearizing central-force systems.
Findings
Closed-form solutions for inverse-square and inverse-cubic forces.
Numerical validation with two-body problem including J2 perturbation.
A new coordinate transformation linked to the particle's local frame.
Abstract
This work introduces a Hamiltonian approach to regularization and linearization of central-force particle dynamics through a new canonical extension of the so-called "projective decomposition". The regularization scheme is formulated within the framework of classic analytical Hamiltonian dynamics as a redundant-dimensional canonical/symplectic coordinate transformation, combined with an evolution parameter transformation, on extended phase space. By considering a generalized version of the standard projective decomposition, we obtain a family of such canonical transformations which differ at the momentum level. From this family of transformations, a preferred coordinate set is chosen that possesses a simple and intuitive connection to the particle's local reference frame. Using this transformation, closed-form solutions are readily obtained for inverse-square and inverse-cubic radial…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsControl and Stability of Dynamical Systems · Numerical methods for differential equations · Dynamics and Control of Mechanical Systems
