Neural Network Inverse Based Omnidirectional Rotation Decoupling Control to the Electrodynamic Reaction Sphere

Z. Huai, Ming Zhang, Yu Zhu, Chen Anlin, Xin Li, Wang Leijie
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Abstract

The electrodynamic reaction sphere is a novel actuator for the spacecraft attitude control subsystem. This paper proposes a neural network inverse based decoupling control scheme to actualize the omnidirectional rotation of the electrodynamic reaction sphere which has strong multivariable nonlinear coupling features due to the induction-based drive. And an integrated electromagnetic torque model of the reaction sphere is firstly derived from the electromagnetic field analysis and modified with the finite element analysis method. Then based on the integrated torque model, a back propagation feedforward neural network is constructed and trained to approach the inverse dynamics which transforms the original system into a pseudo-linear system. Furthermore, an additional PI controller is introduced to achieve good control performance against the unmodelled dynamics. Finally, the effectiveness of the proposed method is validated by simulations.
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基于神经网络逆的电动反应球全向旋转解耦控制
电动反力球是一种用于航天器姿态控制分系统的新型作动器。本文提出了一种基于神经网络逆解耦控制方案,用于实现电动力反应球的全向旋转,该反应球由于感应驱动而具有很强的多变量非线性耦合特性。在电磁场分析的基础上,建立了反力球的整体电磁转矩模型,并用有限元分析方法进行了修正。然后在集成力矩模型的基础上,构造并训练反向传播前馈神经网络,逼近系统的逆动力学,将原系统转化为伪线性系统。此外,还引入了一个额外的PI控制器,以实现对未建模动力学的良好控制性能。最后,通过仿真验证了该方法的有效性。
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