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This chapter presents a control framework designed for rigid-flexible coupling (RFC) satellites subject to multi-source uncertainties. Adopting a set-theoretical perspective, specifically interval analysis, the complex RFC dynamics are modeled by quantifying uncertain physical parameters as bounded intervals. To efficiently compute the uncertainty propagation without high computational costs, an interval-based Linear Quadratic Regulator (LQR) is developed to simultaneously stabilize the satellite's attitude and suppress flexible vibrations. Furthermore, to guarantee operational safety under dynamic conditions, the aforementioned interval-based time-dependent reliability (ITDR) index is integrated as a rigorous constraint within a multi-objective optimization scheme. Numerical simulations validate that this set-based methodology effectively mitigates the effects of uncertainties and coupling disturbances, achieving a superior balance between control performance and system reliability compared to traditional approaches.

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Set Theory-Based Optimal Attitude-Vibration Control for Rigid-Flexible Coupling Satellite

  • 章节

  • 发表日期：

    2026年

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  • Chen Yang,
  • Yuanqing Xia

摘要

This chapter presents a control framework designed for rigid-flexible coupling (RFC) satellites subject to multi-source uncertainties. Adopting a set-theoretical perspective, specifically interval analysis, the complex RFC dynamics are modeled by quantifying uncertain physical parameters as bounded intervals. To efficiently compute the uncertainty propagation without high computational costs, an interval-based Linear Quadratic Regulator (LQR) is developed to simultaneously stabilize the satellite's attitude and suppress flexible vibrations. Furthermore, to guarantee operational safety under dynamic conditions, the aforementioned interval-based time-dependent reliability (ITDR) index is integrated as a rigorous constraint within a multi-objective optimization scheme. Numerical simulations validate that this set-based methodology effectively mitigates the effects of uncertainties and coupling disturbances, achieving a superior balance between control performance and system reliability compared to traditional approaches.