Stacked recurrent neural network based high precision pointing coupled control of the spacecraft and telescopes

Wang, Pei-ji; Zhang, Jinxiu; Lian, Xiaobin; Lu, Lang

doi:10.1016/j.asr.2022.08.072

Cited by 12 publications

(4 citation statements)

References 15 publications

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“…where λ 0 is the stiffness coefficient, λ 1 is the damping coefficient, λ 2 is the velocitydependent damping between the contact surfaces, F c is the coulomb friction force, F s is the static friction force, v is the relative velocity between the contact surfaces, vs. is the Stribeck velocity, u is the average deformation of the contact surface asperities, and g(v) is a function related to the variable v. According to Equation (10), the friction force is a disturbance related to the rotational speed of the pointing mechanism.…”

Section: Nonlinear Friction Torquementioning

confidence: 99%

“…This approach enhances the performance of precision satellite systems and reduces the servo error by a factor of 3.8. Wang et al [10], using a stacked recursive neural network adaptive controller, addressed the issue of insufficient control precision, achieving precise pointing requirements at the nanoradian level between satellites and telescopes. Deng et al [11] designed a frequency-divided controller that coordinates the spacecraft attitude control loop and the telescope attitude control loop, improving the overall performance and pointing stability of the system.…”

Section: Introductionmentioning

confidence: 99%

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Research on High-Stability Composite Control Methods for Telescope Pointing Systems under Multiple Disturbances

Zhang,

Zhao,

Fang

et al. 2024

Sensors

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During the operation of space gravitational wave detectors, the constellation configuration formed by three satellites gradually deviates from the ideal 60° angle due to the periodic variations in orbits. To ensure the stability of inter-satellite laser links, active compensation of the breathing angle variation within the constellation plane is achieved by rotating the optical subassembly through the telescope pointing mechanism. This paper proposes a high-performance robust composite control method designed to enhance the robust stability, disturbance rejection, and tracking performance of the telescope pointing system. Specifically, based on the dynamic model of the telescope pointing mechanism and the disturbance noise model, an H∞ controller has been designed to ensure system stability and disturbance rejection capabilities. Meanwhile, employing the method of an H∞ norm optimized disturbance observer (HODOB) enhances the nonlinear friction rejection ability of the telescope pointing system. The simulation results indicate that, compared to the traditional disturbance observer (DOB) design, utilizing the HODOB method can enhance the tracking accuracy and pointing stability of the telescope pointing system by an order of magnitude. Furthermore, the proposed composite control method improves the overall system performance, ensuring that the stability of the telescope pointing system meets the 10 nrad/Hz1/2 @0.1 mHz~1 Hz requirement specified for the TianQin mission.

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Section: Nonlinear Friction Torquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on High-Stability Composite Control Methods for Telescope Pointing Systems under Multiple Disturbances

Zhang,

Zhao,

Fang

et al. 2024

Sensors

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show abstract

“…The SVAE-GRU model construction Since the degradation data is time series data basically, the temporal feature should be considered in the data generation process. The RNN has proved that the memory function 39,40 can learn the temporal characteristic. Hence, in this paper, the SVAE-GRU is constructed to generate the degradation data.…”

Section: 22mentioning

confidence: 99%

SVAE‐GRU‐based degradation generation and prediction for small samples

Shangguan

Feng

et al. 2023

Quality & Reliability Eng

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The degradation process analysis is the basis of the system reliability assessment. Too few degradation samples will affect the accuracy of the reliability analysis. So, it is necessary to expand the degradation data and construct the degradation prediction model. This paper proposes an SVAE‐GRU‐based degradation generation and prediction model to handle the issues. New degradation data are generated by combining the Stacked Variational Autoencoder (SVAE) and Gated Recurrent Units (GRU) in each time step, which can improve the learning effectiveness of the degradation features. The GRU and the Multi‐layer perceptron calculate the mean and the variance of the degradation distribution for each timestamp, the deeply heterogeneity and temporal feature of the original degraded samples are learned. Then the degradation amount of different samples are predicted. The optimal hyper‐parameters of the SVAE‐GRU are obtained by the grid search method. To verify the effectiveness of the proposed method, three datasets and four methods are used for experiment comparison in this paper. The actual example indicate that the SVAE‐GRU method has the best effect on the degradation generation and prediction.

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“…Basile [15] simulated the precise pointing attitude control of LISA using quaternion feedback based Proportion Integration Differentiation (PID) controller. Wang et al [16] used sliding mode control technique combined with neural network optimization for higher precision pointing control. Deng et al [17] proposed a frequency division control method for high precision line of sight attitude tracking control.…”

Section: Introductionmentioning

confidence: 99%

Constellation attitude tracking control of the space gravitational wave observatory under configuration disturbances

Deng,

Meng

2023

Phys. Scr.

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Space based gravitational wave detectors require a precision relative attitude pointing control in science mode. Their configuration drifts under the influence of perturbations. The spacecraft and telescope optical assembly attitude control loops need to respond to this change in real time. In particular, the constellation reference attitude of the detectors orbiting the earth changes much more than the detectors orbiting the sun, which posing a great challenge to the control system. This article focuses on the constellation attitude tracking problem of the space gravitational wave observatory under configuration disturbances, and systematically analyzes the evolution of the constellation reference attitude. A control method based on finite frequency optimization combine with an improved error-disturbance based observer is proposed. Numerical algorithm simulations show that the method can obtain precise attitude tracking in the measurement bandwidth while effectively suppress the unknown disturbances. Compare with the disturbance based observer controller, the overall error can be reduced by 55% of the original.

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Stacked recurrent neural network based high precision pointing coupled control of the spacecraft and telescopes

Cited by 12 publications

References 15 publications

Research on High-Stability Composite Control Methods for Telescope Pointing Systems under Multiple Disturbances

Research on High-Stability Composite Control Methods for Telescope Pointing Systems under Multiple Disturbances

SVAE‐GRU‐based degradation generation and prediction for small samples

Constellation attitude tracking control of the space gravitational wave observatory under configuration disturbances

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