Adaptive robust sliding mode simultaneous control of spacecraft attitude and micro-vibration based on magnetically suspended control and sensitive gyro

Ren, Yuan; Chen, Xiaocen; Cai, Yuanwen; Wang, Weijie; Liu, Qiang

doi:10.1177/0954410020939790

Cited by 7 publications

(4 citation statements)

References 20 publications

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“…These methods mentioned above focus on how to suspend a rotor stably, but they are not able to ensure MSR has high position accuracy. Because the neural network method can be used to approximate nonlinear functions due to its ability to approximate nonlinear functions [27][28][29][30] and SMC can be used as a special nonlinear controller for its good robustness to parameter changes [31][32][33], it is a good way to use SMC combined with neural networks to control the nonlinear system in MSCMG.…”

Section: Introductionmentioning

confidence: 99%

Neural Network Sliding Model Control of Radial Translation for Magnetically Suspended Rotor (MSR) in Control Moment Gyro

et al. 2023

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For a magnetically suspended control moment gyro (MSCMG), the high-speed rotor is actively suspended by magnetic bearings of 5-DOF, but the nonlinearity of the magnetic suspension force is one of the main reasons for the poor accuracy of radial translation control of the magnetically suspended rotor (MSR). To solve this problem, here, the characteristics of the magnetic suspension force are analyzed, and the nonlinear dynamic model of MSR is established. A sliding mode control (SMC) based on a neural network is presented, and the radial basis function (RBF) neural network is adopted to approximate the nonlinear displacement stiffness and the current displacement stiffness to weaken the chattering in SMC to improve the control accuracy of the MSR. The stability of the neural network SMC for the MSR is analyzed based on Lyapunov functions, and the rules of updating network weights are presented based on adaptive algorithms. Compared with these existing classic control methods, the simulation and experimental tests performed on a single-gimbal MSCMG with an angular momentum of 200 N.m.s indicated that this neural network SMC for MSR’s radial translation can not only make its suspension more stable but can also make its position precision higher.

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Section: Introductionmentioning

confidence: 99%

Neural Network Sliding Model Control of Radial Translation for Magnetically Suspended Rotor (MSR) in Control Moment Gyro

et al. 2023

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Section: Introductionmentioning

confidence: 99%

“…The modern control methods compensate for the disturbances, and could be classified into observer-based compensation methods and direct compensation methods. The main processes of the observer-based compensation methods are as follows 16,17 : (1) design the observers aiming at the different characteristics of the disturbances and (2) compensate for the observed disturbances to eliminate the effects of the disturbances. In the direct compensation methods, there are no observer designing processes, and the disturbances are estimated and compensated for directly.…”

Section: Introductionmentioning

confidence: 99%

Integrated control scheme for a large membrane diffractive space telescope

Tang

Guo

Feng

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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For higher resolution, next-generation space telescopes would be equipped with 10–20 m scale membrane diffractive primary lenses, and would have 100 m scale focal length. The large and flexible structure makes high-accuracy and high-stability control a great challenge. Specifically, both high-frequency and low-frequency disturbances must be attenuated, and the relative motion between the primary lens and the receiver (composed of the correcting optics and the imaging sensor) must be controlled. This paper presents a novel integrated control scheme to achieve the strict control goals. The dynamic model of a membrane diffractive space telescope is presented, where both high-frequency and low-frequency disturbances are considered. Nonlinear deformation of the flexible structure is also taken into account. The integrated control scheme consists of 3 parts: (1) an Agile Stable Precision platform (ASP), which can not only reduce the high-frequency vibrations for the receiver but also act as the actuator in the receiver control system; (2) a neural network controller for the spacecraft bus, which control the attitude of the spacecraft bus under uncertain low-frequency disturbances; (3) a finite-time neural network controller for the receiver to make the relative position and attitude of the receiver track on the expected state as fast as possible. Numerical simulations were carried out to verify the superiority of the integrated control scheme. Compared with traditional single stage spacecraft control (i.e., without the ASP), the accuracy and stability of the relative position and attitude are improved by at least one order of magnitude, and the settling time is greatly reduced.

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“…Spacecraft attitude control has become a crucial technique and a prosperous topic over the past few decades. Adaptive control, 1,2 sliding mode control, [3][4][5] and backstepping method 6,7 are utilized to develop various attitude control strategies. Parametric uncertainties and actuator faults of a rigid spacecraft are taken into account, and an integral sliding mode manifold is employed to derive the attitude tracking control law.…”

Section: Introductionmentioning

confidence: 99%

Velocity-free attitude tracking for rigid spacecraft via bounded control

Zhang

Liu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part G:

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This article investigates the attitude tracking control problem for a rigid spacecraft without angular velocity feedback, in which external disturbances, parametric uncertainties, and input saturation are considered. Initially, an angular velocity observer is developed incorporated with adaptive technique, which could tackle the unmeasurable angular velocity and system uncertainties simultaneously. By introducing adaptive updating law into the proposed observer, the synchronized uncertainties are handled such that robustness of the observer is enhanced, even in the presence of external disturbances. Further, for solving the input constraints problem, command filter and backstepping method are utilized; thus, a bounded attitude tracking control law is derived. Finally, the attitude tracking performance is evaluated by numerical examples.

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Adaptive robust sliding mode simultaneous control of spacecraft attitude and micro-vibration based on magnetically suspended control and sensitive gyro

Cited by 7 publications

References 20 publications

Neural Network Sliding Model Control of Radial Translation for Magnetically Suspended Rotor (MSR) in Control Moment Gyro

Neural Network Sliding Model Control of Radial Translation for Magnetically Suspended Rotor (MSR) in Control Moment Gyro

Integrated control scheme for a large membrane diffractive space telescope

Velocity-free attitude tracking for rigid spacecraft via bounded control

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