Disturbance-observer-based fixed-time control for 6-DOF spacecraft rendezvous and docking operations under full-state constraints

• Published in: Acta astronautica Vol. 205; pp. 225 - 238
• Main Authors: Zhang, Yu-chen, Ma, Meng-chen, Yang, Xiao-Yan, Song, Shen-min
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2023
• Subjects: Adaptive neural network; Disturbance observer; Fixed-time; Full-state constraint; Input saturation; Adaptive neural network; Disturbance observer; Input saturation; Fixed-time; Full-state constraint
• ISSN: 0094-5765
• DOI: 10.1016/j.actaastro.2023.02.005

The problem of fixed-time control is addressed for the autonomous proximity of non-cooperative targets with full-state constraints, input saturation, parameter uncertainties, and matched and unmatched disturbances. A six degrees of freedom (6-DOF) relative motion model for non-cooperative targets is constructed. Combining with a radial basis function neural network (RBF-NN), a fixed-time disturbance observer is proposed to estimate system disturbances. Model items and assumptions for the boundedness of the derivatives of the disturbances are not required in the proposed disturbance observer. The back-stepping technique provides an adaptive fixed-time controller to stabilize the full-state constrained relative error system and a unified framework for dealing with constrained and unconstrained cases is proposed by designing a coordinate transformation method. The fixed-time stability of the relative error system is guaranteed by the proposed controller regardless of the constraints. Finally, two simulation scenarios validate the effectiveness and robustness of the developed controller design. •A fixed-time neural network disturbance observer is presented to estimate disturbances with high frequency noise.•A unified coordinate transformation theory is proposed for the full-state constrained system.•An anti-saturation fixed time controller is designed to achieve spacecraft autonomous rendezvous and docking task.