Abstract Momentum management of spacecraft aims to avoid the angular momentum accumulation of control momentum gyros through real-time attitude adjustment. An attitude control/momentum management controller based on state-dependent Riccati equation is developed for attitude-stabilized spacecraft. The governing equations of the system are formulated as three-axis coupled with full moment of inertia, which fully capture the nonlinearity of the system and are valid for systems with significant products of inertia or strong pitch to roll/yaw coupling. The state-dependent Riccati equation algorithm brings the nonlinear system to a linear structure having state dependent coefficients matrices and minimizing a quadratic-like performance index. The system equations are nondimensionalized, which avoid numerical problems at the same time make the weighting matrix more predictable. To guarantee closed-loop system stability, the state-dependent Riccati equation algorithm is also modified based on pole placement technique. The state-dependent Riccati equation is online calculated through the computational-efficient θ-D technique which reaches a tradeoff between control optimality and computation load. The dynamic characteristics of the system at torque equilibrium attitude are analyzed. Constraints on moment of inertia for successful momentum management are provided. Simulations demonstrate the excellent performance of the controller.

    Highlights A momentum management controller using stability-based SDRE method is developed. The controller is effective for system with strong pitch-to-roll/yaw coupling. θ-D method reaches a tradeoff between optimality and simplicity in solving SDRE. Constrains on moment of inertia for momentum management in LVLH are presented.


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    Title :

    Stability-based SDRE controller for spacecraft momentum management


    Contributors:
    Zhu, Mengping (author) / Xu, Shijie (author)

    Published in:

    Acta Astronautica ; 89 ; 71-82


    Publication date :

    2013-03-29


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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