Abstract Spacecraft are required to achieve fast attitude reorientation in many space missions. However, the attitude maneuver will be limited by the bounded and pointing constraints. The presence of these complex multiaxis constraints will largely reduce the feasible attitude space and greatly degrade the solving efficiency of the planning algorithm. For the time-optimal spacecraft reorientation problem under multiaxis constraints, a new heuristic decomposition planning on the virtual domain (HDPV) method is proposed in this paper. The parameterized attitude path is first determined on the virtual domain. Then the virtual-domain-based variable-step approach is presented to rapidly check the pointing constraints and generate the sets of candidate rotational-path decomposition nodes. The composite-position heuristics is developed to select the best node during the decomposition optimization, which considers the maneuver time and connection smoothness of paths. The total continuous parameterized path under keep-out and keep-in constraints is yielded through recursive planning. Finally, the time-optimal path parameterization approach is adopted to minimize the maneuver time along the total path and generate a fast attitude trajectory under bounded constraints on the time domain. Simulation results demonstrate the high computational efficiency and good optimization effect of the proposed method.

    Highlights Propose the heuristic decomposition planning on the virtual domain method. New virtual-domain-based variable-step approach and composite-position heuristics. Address the time-optimal problem under multiaxis constraints. The HDPV method has a high computational efficiency. Generate a fast spacecraft reorientation trajectory.


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    Titel :

    Heuristic decomposition planning for fast spacecraft reorientation under multiaxis constraints


    Beteiligte:
    Wang, Hui (Autor:in) / Xu, Rui (Autor:in)

    Erschienen in:

    Acta Astronautica ; 198 ; 286-294


    Erscheinungsdatum :

    2022-06-09


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch