Intrinsic Successive Convexification: Trajectory Optimization on Smooth Manifolds

A fundamental issue at the core of trajectory optimization on smooth manifolds is handling the implicit manifold constraint within the dynamics. The conventional approach is to enforce the dynamic model as a constraint. However, we show this approach leads to significantly redundant operations, as well as being heavily dependent on the state space representation. Specifically, we propose an intrinsic successive convexification methodology for optimal control on smooth manifolds. This so-called iSCvx is then applied to a representative example involving attitude trajectory optimization for a spacecraft subject to non-convex constraints.

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Publication Details

Journal
IEEE Control Systems Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lcsys.2025.3571671
Primary Topic
Optimization and Variational Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Intrinsic Successive Convexification: Trajectory Optimization on Smooth Manifolds

Mehran Mesbahi, Behçet Açıkmeşe, Spencer Kraisler
IEEE Control Systems Letters
Optimization and Variational Analysis
article

Intrinsic Successive Convexification: Trajectory Optimization on Smooth Manifolds

Mehran Mesbahi, Behçet Açıkmeşe, Spencer Kraisler
article en

Abstract

A fundamental issue at the core of trajectory optimization on smooth manifolds is handling the implicit manifold constraint within the dynamics. The conventional approach is to enforce the dynamic model as a constraint. However, we show this approach leads to significantly redundant operations, as well as being heavily dependent on the state space representation. Specifically, we propose an intrinsic successive convexification methodology for optimal control on smooth manifolds. This so-called iSCvx is then applied to a representative example involving attitude trajectory optimization for a spacecraft subject to non-convex constraints.

IEEE Control Systems LettersVol. 9
University of Washington (US), American Institute of Aeronautics and Astronautics (US)
National Aeronautics and Space Administration, Air Force Office of Scientific Research
Openalex Percentile: Top 88%
Optimization and Variational Analysis
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