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On-line attitude perturbation estimation in the earth-orbiting satellite

机译：地球轨道卫星的在线姿态摄动估计

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This paper presents three innovative techniques to estimate external perturbation torques acting on an Earth-orbiting satellite. The proposed techniques overcome the problem of derivative reconstruction from noisy measurement in the estimation procedure of the environmental perturbation torques. For this purpose, in the first technique, known as nonlinear disturbances observer (NDO) technique, derivative term is eliminated in the estimation equations by employing auxiliary variable vector and by selecting appropriate design parameters. In the second proposed approach, the robust exact differentiation via second-order sliding mode theory, known as Levant differentiator, is employed to decrease derivative estimation error in the process of estimation. To improve the performance of the Levant differentiator, the final innovative approach, known as sub-band adaptive robust differentiator (SARD) technique, is proposed in which the derivative term in the estimation process is reconstructed by using Levant differentiator and sub-band adaptive filter theory. In the SARD technique, the original noisy measurement signal is divided into sub-band signals and then, the Levant differentiator is applied to each sub-band signals to construct exact differentiator from noisy measurement. The novel aspect of paper is employing second-order sliding mode theory in the sub-bands frequency to improve the performance of derivative reconstruction in the presence of measurement noise. In this regard, a nonlinear model of the earth orbiting satellite is simulated using specific navigation disturbances and the results verified the feasibility of the proposed strategies. (C) 2017 Elsevier Masson SAS. All rights reserved.
机译：本文提出了三种创新技术来估算作用在地球轨道卫星上的外部扰动扭矩。所提出的技术克服了在环境扰动转矩的估计过程中从噪声测量得到的导数重建的问题。为此，在称为非线性干扰观测器（NDO）技术的第一种技术中，通过采用辅助变量矢量并选择适当的设计参数，可以在估计方程中消除导数项。在提出的第二种方法中，采用了通过二阶滑模理论的鲁棒精确差分法（称为黎凡特微分器）来减少估计过程中的导数估计误差。为了提高黎凡特微分器的性能，提出了一种最终的创新方法，即子带自适应鲁棒微分器（SARD）技术，其中，利用黎凡特微分器和子带自适应滤波器在估计过程中重建了导数项。理论。在SARD技术中，将原始的噪声测量信号分为子带信号，然后将Levant微分器应用于每个子带信号，以从噪声测量中构造出精确的微分器。本文的新颖之处在于在子带频率中采用二阶滑模理论来改善在存在测量噪声的情况下微分重构的性能。在这方面，使用特定的导航干扰对地球轨道卫星的非线性模型进行了仿真，结果验证了所提出策略的可行性。 （C）2017 Elsevier Masson SAS。版权所有。

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