Adaptive finite time distributed 6-DOF synchronization control for spacecraft formation without velocity measurement
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In this paper, the problem of distributed finite time six-degree-of-freedom (6-DOF) synchronization control for spacecraft formation flying (SFF) with the external disturbances and parameter uncertainties is investigated. Firstly, a continuous adaptive finite time distributed control protocol with full state feedback is proposed, which can overcome the chattering problem and reduce the convergence time in the reaching phase. Subsequently, an adaptive sliding mode observer with finite time convergence is designed to estimate the velocity information. Then a new observer-based continuous adaptive finite time distributed control protocol is designed. Rigorous proofs show that these two distributed controllers both can guarantee that the attitude and relative position tracking errors can converge to the origin within finite time rather than the bounded regions around the origins. Finally, the effectiveness of the designed distributed control protocols is demonstrated by simulation results.
KeywordsSpacecraft formation system 6-DOF synchronization control Finite time convergence Adaptive control Without velocity measurement
This work was supported by the NSFC (61327807,61521091, 61520106010, 61134005) and the National Basic Research Program of China (973 Program: 2012
CB821200, 2012CB821201), and the Academic Excellence Foundation of BUAA for PhD Students.
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Conflict of interest
The authors declared that they have no conflict of interest.
- 41.Moreno, J.A., Osorio, M.A.: Lyapunov approach to second-order sliding mode controllers and observers. In: Proceedings of the 47th IEEE Conference on Decision and Control, pp. 2856–2861 (2008)Google Scholar
- 44.Besancon G.: An overview on observer tools for nonlinear systems. In: Nonlinear Observers and Applications. Springer, Berlin, Heidelberg, pp. 1–33 (2007)Google Scholar
- 45.Zhang A., Li Y.: A modified unscented Kalman filter for autonomous navigation of distributed satellite systems. In: IEEE Proceedings of the Chinese Control Conference, pp. 5811–5816 (2017)Google Scholar