装载大型挠性附件的航天器鲁棒模型预测控制

Robust Model Predictive Control for Spacecraft with Large Flexible Appendages

  • 摘要: 针对装载有大型挠性附件的航天器,其挠性附件转动惯量占系统绝大比例,导致航天器刚柔耦合效应显著加剧,易激发挠性振动,严重影响姿态控制甚至造成系统失稳,对此,设计了自适应鲁棒模型预测控制策略。首先,将扰动观测器与鲁棒模型预测控制相结合,对由挠性振动构成的复合扰动进行在线估计,在此基础上设计标称系统优化问题,通过求取最优控制序列,以有效抑制大挠性附件振动对姿态控制系统的影响;其次,采用基于神经动力学优化理论的简化对偶神经网络高效求解优化问题,可有效降低计算复杂度,提升姿态控制系统的响应速度;最后,通过设计自适应滑模辅助补偿控制律,以进一步抑制挠性扰动的观测误差等残余扰动对姿态的干扰,从而确保实际系统状态跟踪标称状态轨迹。仿真结果表明,所设计的控制策略能够有效抑制大挠性附件振动并实现航天器姿态快速收敛。

     

    Abstract: Aiming at spacecraft equipped with large flexible appendages, the moment of inertia of these appendages constitutes a substantial proportion of the total system, resulting in a significantly accentuated rigid-flexible coupling effect. The pronounced coupling effect can easily excites flexible vibration that severely degrade attitude control performance and may even lead to system instability. In order to address this problem, an adaptive robust model predictive control strategy is designed. First, a disturbance observer is integrated with robust model predictive control to estimate the composite disturbance arising from flexible vibration online. Based on this estimation, a nominal system optimization problem is formulated to solve the optimal control sequence, thereby effectively reducing the impact of large flexible vibration on the attitude system. Second, a simplified dual neural network based on neurodynamic optimization theory is employed to solve the optimization problem efficiently, significantly reducing computational complexity and accelerating the response of the attitude control system. Finally, an adaptive sliding mode auxiliary compensation control law is designed to further reduce the error in observing the flexible vibration and other residual disturbance. Consequently, the actual system state closely tracks the nominal state trajectory. Simulation results show that the designed control strategy can effectively suppress vibration of the large flexible appendages while achieving rapid convergence of the spacecraft attitude.

     

/

返回文章
返回