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基于卡尔曼滤波的输出调节自适应无拖曳控制

Output Regulation Adaptive Drag-Free Control via Kalman Filter

  • 摘要: 针对一类仅能获得系统降维输出信息的自适应输出调节控制问题,提出了一种基于卡尔曼滤波的输出调节模型参考自适应控制方法,利用卡尔曼滤波的非线性估计能力,实现降维输出量测信息向全维状态信息的估计,利用观测状态实现闭环系统输出向参考状态的自适应跟踪,并确保各闭环信号的稳定性。将上述方法应用于空间引力波探测任务无托曳稳定平台的控制问题中,实现无托曳控制系统在面临系统参数未知及附加干扰时稳定的输出跟踪能力。基于Lyapunov方法实现各闭环信号稳定性的理论分析,数值仿真对比验证了该方法相对于一般输出调节自适应控制方法跟踪能力的优越性。

     

    Abstract: For a kind of adaptive output regulation control that can only obtain the reduced dimension output information of the system, in this paper, a model reference adaptive control method for output regulation based on Kalman filter was proposed, which used the nonlinear estimation ability of Kalman filter to realize the estimation of output measurement information to full dimensional state information, and used the observation state to realize adaptive tracking of the output of closed-loop system to the reference state to ensure the stability of each closed-loop signal. The above method was applied to the control of the drag-free stable platform in the space gravitational wave detection mission, and the stable output tracking ability of the drag-free control system was realized with unknown parameters and additional disturbances. Based on the theoretical analysis of each closed-loop signal stability realized by the Lyapunov method, numerical simulation comparison verifies the effectiveness of the method over the tracking ability of the general output tracking adaptive control method.

     

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