In this paper, an adaptive artificial potential function (AAPF) method is developed for spacecraft formation reconfiguration with multi-obstacle avoidance under navigation and control uncertainties. Furthermore, an improved Linear Quadratic Regular (ILQR) is proposed to track the reference trajectory and a Lyapunov-based method is employed to demonstrate the stability of the overall closed-loop system. Compared with the traditional APF method and the equal-collision-probability surface (ECPS) method, the AAPF method not only retains the advantages of APF method and ECPS method, such as low computational complexity, simple analytical control law and easy analytical validation progress, but also proposes a new APF to solve multi-obstacle avoidance problem considering the influence of the uncertainties. Moreover, the ILQR controller obtains high control accuracy to enhance the safe performance of the spacecraft formation reconfiguration. Finally, the effectiveness of the proposed AAPF method and the ILQR controller are verified by numerical simulations.
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The work was supported by the Major Program of National Nature Science Foundation of China (Grant Nos. 61690210 and 61690213, the National Science Foundation of China (Grant Nos. 11725211, 61503414, 11302253, and 11702320), and the Scientific Research Project of National University of Defense Technology (ZK16-03-20).
Yi Wang was born in Huaihua, Hunan Provice, China, in 1990. He received his B.S. degree in aerospace engineering from the Northwestern Polytechnical University, China, in 2012, and the M.S. degree in aerospace engineering from Central South University, China, in 2015. He is currently pursuing his Ph.D. degree in aerospace engineering with the National University of Defense Technology, China. His current research interests include spacecraft dynamics, navigation and control.
Xiaoqian Chen received his M.S. and Ph.D. degrees in aerospace engineering from National University of Defense Technology, China, in 1997 and 2001, respectively. He is currently a professor and the dean of National Institute of Defense Technology Innovation, Beijing, China. His current research interests include spacecraft systems engineering, advanced digital design methods of space systems, and multidisciplinary design optimization.
Dechao Ran received his M.S. and Ph.D. degrees in aerospace engineering from National University of Defense Technology, China, in 2013 and 2017, respectively. He is currently an assistant research fellow in National Institute of Defense Technology Innovation, China. He joined the McGill University as a visiting Ph.D. student from 2015 to 2016, and focused on the dynamics and control of spacecraft formation. His research interests include the areas of spacecraft formation dynamics and control, satellite control system design. Moreover, he has the interest of nano-satellite design and launch experiences.
Yong Zhao received his Ph.D. degree in aerospace engineering from National University of Defense Technology, China, in 2007. He is currently a professor in National University of Defense Technology, China. His current research interests include spacecraft systems engineering, advanced digital design methods of space systems, and multidisciplinary design optimization.
Yang Chen received his B.S. degree in aerospace engineering from the National University of Defense Technology, China, in 2017. He is currently pursuing his M.S. degree in aerospace engineering with the National University of Defense Technology, China. His current research interests include optimal theory, aerospace engineering and dynamics.
Yuzhu Bai received his Ph.D. degree in aerospace engineering from National University of Defense Technology, China, in 2010. He is currently an associate professor at National University of Defense Technology, China. His current research interests include micro-satellite design, spacecraft dynamics and control.
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Wang, Y., Chen, X., Ran, D. et al. Spacecraft formation reconfiguration with multi-obstacle avoidance under navigation and control uncertainties using adaptive artificial potential function method. Astrodyn 4, 41–56 (2020). https://doi.org/10.1007/s42064-019-0049-x
- spacecraft formation flying
- spacecraft formation reconfiguration
- collision avoidance
- artificial potential function