An Efficient iLQR Algorithm for Optimal Control with Bounded States and Inputs: Application to Spacecraft Maneuvers
Abstract
This paper presents a constrained iterative Linear Quadratic Regulator (Box-iLQR) method for nonlinear aerospace optimal-control problems with bounded states and controls. Logarithmic barrier functions are used with a two-fold objective: the barrier parameter is reduced toward zero to recover the constrained optimal trajectory, while a finite barrier is retained to construct a smooth, constraint-aware feedback policy for closed-loop operation. The method is demonstrated on spacecraft attitude control, a minimum-fuel planar orbit transfer, and an L2 to L2 halo-orbit transfer. Box-iLQR respects the imposed constraints and produces nominal trajectories together with time-varying feedback policies. Closed-loop simulations under disturbance, measurement noise, and control uncertainty show substantial reductions in terminal error. These results demonstrate that Box-iLQR provides both high-accuracy constrained trajectory optimization and practical constraint-aware feedback within a single framework.
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BibTeX
@misc{abhijeet2026efficient,
title = {{An Efficient iLQR Algorithm for Optimal Control with Bounded States and Inputs: Application to Spacecraft Maneuvers}},
author = {Abhijeet and Suman Chakravorty},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.32075},
eprint = {2609.32075},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.32075},
note = {CC0},
}
RIS
TY - UNPB
TI - An Efficient iLQR Algorithm for Optimal Control with Bounded States and Inputs: Application to Spacecraft Maneuvers
AU - Abhijeet
AU - Suman Chakravorty
PY - 2026
DA - 2026/09/25
PB - arXiv
DO - 10.48550/arxiv.2609.32075
UR - https://arxiv.org/abs/2609.32075
AB - This paper presents a constrained iterative Linear Quadratic Regulator (Box-iLQR) method for nonlinear aerospace optimal-control problems with bounded states and controls. Logarithmic barrier functions are used with a two-fold objective: the barrier parameter is reduced toward zero to recover the constrained optimal trajectory, while a finite barrier is retained to construct a smooth, constraint-aware feedback policy for closed-loop operation. The method is demonstrated on spacecraft attitude control, a minimum-fuel planar orbit transfer, and an L2 to L2 halo-orbit transfer. Box-iLQR respects the imposed constraints and produces nominal trajectories together with time-varying feedback policies. Closed-loop simulations under disturbance, measurement noise, and control uncertainty show substantial reductions in terminal error. These results demonstrate that Box-iLQR provides both high-accuracy constrained trajectory optimization and practical constraint-aware feedback within a single framework.
ER -