Observability-Aware Differential Dynamic Programming with Impulsive Maneuvers

In autonomous space systems, the reliability of navigation systems is essential. Observability in autonomous orbit determination techniques depends on the spacecraft’s orbital motion, making the design of autonomous navigation systems and orbital maneuvers a coupled process. This study develops a stable and efficient algorithm based on differential dynamic programming to design maneuver sequences that improve navigation performance. Our approach incorporates the Fisher information matrix into a cost function to quantify state observability and facilitates its convergence using a semi-analytic gradient and Hessian derived under impulsive maneuvers. Two numerical examples show the validity and effectiveness of our algorithm. The results indicate the stability and efficiency in determining maneuver sequences and the improvement of state estimation accuracy along an optimized trajectory. It is also applicable to other observability-aware optimal control problems because the algorithm is independent of specific systems.

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Publication Details

Journal
Journal of Guidance Control and Dynamics
Published
2024-09-01
DOI
https://doi.org/10.2514/1.g007798
Citations
4
Primary Topic
Adaptive Dynamic Programming Control
Type
article
Field-Weighted Citation Impact
1.45

Funders

Controls
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article

Observability-Aware Differential Dynamic Programming with Impulsive Maneuvers

Masahiro Fujiwara, Ryu Funase
4 citations
Journal of Guidance Control and Dynamics
Adaptive Dynamic Programming Control
1.45
article

Observability-Aware Differential Dynamic Programming with Impulsive Maneuvers

Masahiro Fujiwara, Ryu Funase
article en
4 citations

Abstract

In autonomous space systems, the reliability of navigation systems is essential. Observability in autonomous orbit determination techniques depends on the spacecraft’s orbital motion, making the design of autonomous navigation systems and orbital maneuvers a coupled process. This study develops a stable and efficient algorithm based on differential dynamic programming to design maneuver sequences that improve navigation performance. Our approach incorporates the Fisher information matrix into a cost function to quantify state observability and facilitates its convergence using a semi-analytic gradient and Hessian derived under impulsive maneuvers. Two numerical examples show the validity and effectiveness of our algorithm. The results indicate the stability and efficiency in determining maneuver sequences and the improvement of state estimation accuracy along an optimized trajectory. It is also applicable to other observability-aware optimal control problems because the algorithm is independent of specific systems.

Journal of Guidance Control and DynamicsVol. 47(9)
Japan Aerospace Exploration Agency (JP), The University of Tokyo (JP)
Japan Society for the Promotion of Science
Affordable and clean energy
Openalex Percentile: Top 16%
Adaptive Dynamic Programming Control
1.45
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