This article introduces the problem of predefined-time attitude takeover control for spacecraft. A novel radial basis function neural network predefined-time extended state observer is presented, which facilitates estimation of external disturbance, unmeasurable angular velocity, and actuator installation deviation within a predefined-time. A quantizer is then employed to quantize control input signal in controller-to-actuator side to mitigate communication pressure. Thereafter, a novel predefined-time attitude controller is proposed to ensure system states converge within a predefined-time. Finally, the effectiveness of the proposed control scheme is substantiated via numerical simulation.
Attitude takeover control of spacecraft based on neural network predefined‐time extended state observer
Bernelli‐Zazzera, Franco
2024-01-01
Abstract
This article introduces the problem of predefined-time attitude takeover control for spacecraft. A novel radial basis function neural network predefined-time extended state observer is presented, which facilitates estimation of external disturbance, unmeasurable angular velocity, and actuator installation deviation within a predefined-time. A quantizer is then employed to quantize control input signal in controller-to-actuator side to mitigate communication pressure. Thereafter, a novel predefined-time attitude controller is proposed to ensure system states converge within a predefined-time. Finally, the effectiveness of the proposed control scheme is substantiated via numerical simulation.File | Dimensione | Formato | |
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