Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-28T19:26:25.887Z Has data issue: false hasContentIssue false
  • English
  • Français

Multi-Equal-Collision-Probability-Cure Method for Convex Polygon-shape Spacecraft Safe Proximity Manoeuvres

Published online by Cambridge University Press:  27 September 2018

Wang Yi ,
Chen Xiaoqian ,
Ran Dechao ,
Ou Yangwei Open the ORCID record for Ou Yangwei [Opens in a new window] ,
Ni Qing  and
Bai Yuzhu
Wang Yi
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, People's Republic of China)
Chen Xiaoqian
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, People's Republic of China)
Ran Dechao
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, People's Republic of China)
Ou Yangwei
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, People's Republic of China)
Ni Qing
Affiliation:
(Manned Space System Research Center, Beijing 10000, People's Republic of China)
Bai Yuzhu*
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, People's Republic of China)
*
(E-mail: baiyuzhu@hotmail.com)
Get access Rights & Permissions [Opens in a new window]

Abstract

In this paper, the spacecraft close-range safe proximity problem is investigated. In the presence of a “chief” spacecraft, a Multi-Equal-Collision-Probability-Curve (MECPC) method is developed. The influence of the chief spacecraft with a convex polygon shape is considered and the chief spacecraft is divided into several small components. Each component generates a corresponding separate repulsive force and the superposition of these forces is regarded as the ultimate avoidance force. As a result, the proposed MECPC method not only improves the system robustness against control and navigation uncertainties but is also analytically validated in collision avoidance. The MECPC method solves the safe proximity problem in the presence of a convex polygon shape. In addition, an Improved Linear Quadratic Regulator (ILQR) is designed to track the expected trajectory. Numerical simulations are performed in a close-range operation environment to verify the effectiveness of the proposed MECPC method.

Keywords

Collision AvoidanceConvex ShapesClose-range ProximityCollision Probability DensityEqual Collision Probability Curve
Type
Research Article
Information
The Journal of Navigation , Volume 72 , Issue 2 , March 2019 , pp. 405 - 429
Copyright
Copyright © The Royal Institute of Navigation 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Alfano., S. (2006a). Satellite Collision Probability Enhancements. Journal of Guidance, Control, and Dynamics, 29(3), 588–592.Google Scholar
Alfano., S. (2006b). Addressing Nonlinear Relative Motion for Spacecraft Collision Probability. In: AIAA/AAS Astrodynamics Specialist Conference and Exhibit, Keystone, Colorado, AIAA paper 2006–6760.Google Scholar
Bai, X. Z., Chen, L. and Tang, G. J. (2013). Explicit Expression of Collision Probability in terms of RSW and NTW components of relative position. Advances in Space Research, 52(6), 1078–1096.Google Scholar
Bai, X. Z., Ma, C. W., Chen, L. and Tang, G. J. (2016). Maximum Collision Probability considering Variable Size, Shape, and Orientation of Covariance Ellipse. Advances in Space Research, 58(6), 950-966.Google Scholar
Bevilacqua, R., Lehmann, T. and Romano, M. (2011). Development and Experimentation of LQR/APF Guidance and Control for Autonomous Proximity Maneuvers of Multiple Spacecraft. Acta Astronautica, 68(7), 1260–1275.Google Scholar
Cao, L., Chen, X. Q. and Misra, A. K. (2014). Minimum Sliding Mode Error Feedback Control for Fault Tolerant Reconfigurable Satellite Formation with J2 Perturbation. Acta Astronautica, 96, 201–216.Google Scholar
Cao, L., Qiao, D. and Xu, J. W. (2018a). Suboptimal Artificial Potential Function Sliding Mode Control for Spacecraft Rendezvous with Obstacle Avoidance. Acta Astronautica, 143, 133–146.Google Scholar
Cao, L., Qiao, D. and Chen, X. Q. (2018b). Laplace ℓ1 Huber Based Cubature Kalman Filter for Attitude Estimation of Small Satellite. Acta Astronautica, 148, 48–56.Google Scholar
Chen, Q., Yin, C., Zhou, J., Wang, Y., Wang, X. Y. and Chen, C. Y. (2018). Hybrid Consensus-based Cubature Kalman Filtering for Distributed State Estimation in Sensor Networks. IEEE Sensors Journal, 18(11), 4561–4569.Google Scholar
Demars, K. J., Cheng, Y. and Jah, M. K. (2014). Collision Probability with Gaussian Mixture Orbit Uncertainty. Journal of Guidance, Control, and Dynamics, 37(3), 979–985.Google Scholar
Flores-Abad, A., Ma, O., Pham, K. and Ulrich, S. (2014). A Review of Space Robotics Technologies for On-orbit Servicing. Progress in Aerospace Science, 68, 1–26.Google Scholar
Ge, S. S., Cui, Y. J. (2002). Dynamic Motion Planning for Mobile Robots using Potential Field Method. Autonomous Robots, 13(3), 207–222.Google Scholar
Huang, X., Yan, Y., Zhou, Y. and Yang, Y. N. (2017a). Dual-quaternion based Distributed Coordination Control of Six-DOF Spacecraft Formation with Collision Avoidance. Aerospace Science and Technology, 67, 443–455.Google Scholar
Huang, X., Yan, Y. and Zhou, Y. (2017b). Underactuated Spacecraft Formation Reconfiguration with Collision Avoidance. Acta Astronautica, 131, 166–181.Google Scholar
Lin, F. (2007). Robust Control Design an Optimal Control Approach. John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, England, Ch. 5.Google Scholar
Luo, Y. Z., Liang, L. B., Wang, H. and Tang, G. J. (2011). Quantitative Performance for Spacecraft Rendezvous Trajectory Safety. Journal of Guidance, Control, and Dynamics, 34(4), 1264–1269.Google Scholar
Luo, Y. Z. and Yang, Z. (2017). A Review of Uncertainty Propagation in Orbital Mechanics. Progress in Aerospace Sciences, 89, 23–39.Google Scholar
Nag, S. and Summerer, L. (2013). Behaviour based, Autonomous and Distributed Scatter Manoeuvres for Satellite Swarms. Acta Astronautica, 82(1), 95–109.Google Scholar
Ni, Q., Huang, Y. Y. and Chen, X. Q. (2016). Nonlinear Control of Spacecraft Formation Flying with Disturbance Rejection and Collision Avoidance. Chinese Physics B, 26(7), 014502.Google Scholar
Ou, Y. W. and Zhang, H. B. (2017a). Observability-based Mars Autonomous Navigation Using Formation Flying Spacecraft. Journal of Navigation, 71(1), 21–43.Google Scholar
Ou, Y. W. and Zhang, H. B. (2017b). Mars Final Approach Navigation using Ground Beacons and Orbiters: An Information Propagation Perspective. Acta Astronautica, 138, 490–500.Google Scholar
Palacios, L., Ceriotti, M. and Radice, G. (2015). Close Proximity Formation Flying via Linear Quadratic Tracking Controller and Artificial Potential Function. Advances in Space Research, 56(10), 2167–2176.Google Scholar
Patera, R. P. (2003). Satellite Collision Probability for Nonlinear Relative Motion. Journal of Guidance, Control, and Dynamics, 26(5), 728–733.Google Scholar
Patera, R. P., (2006). Collision Probability for Larger Bodies Having Nonlinear Relative Motion. Journal of Guidance, Control, and Dynamics, 29(6), 1468–1472.Google Scholar
Peynot, T., Lui, S. T., McAllister, R., Fitch, R. and Sukkarieh, S. (2014). Learned stochastic mobility prediction for planning with control uncertainty on unstructured terrain. Journal of Field Robotics, 31(6), 969–995.Google Scholar
Psiaki, M. L. (2011). Absolute orbit and gravity determination using relative position measurements between two satellites. Journal of Guidance, Control, and Dynamics, 34(5), 1285–1297.Google Scholar
Serra., R., Arzelier, D., Joldes, M., Lasserre, J. B., Rondepierre, A. and Salvy, B. (2016). Fast and Accurate Computation of Orbital Collision Probability for Short-Term Encounters. Journal of Guidance, Control, and Dynamics, 39(5), 1009–1021.Google Scholar
Shan, M. H., Guo, J. and Gill, E. (2016). Review and Comparison of Active Space Debris Capturing and Removal Methods. Progress in Aerospace Science, 80, 18–32.Google Scholar
Spencer, D. A., Chait, S. B., Schulte, P. Z. and Okseniuk, K. J. (2016). Prox-1 University-Class Mission to Demonstrate Automated Proximity Operations. Journal of Spacecraft and Rockets, 53(5), 847–863.Google Scholar
Sun, Z. J., Luo, Y. Z. and Niu, Z. Y. (2014). Spacecraft Rendezvous Trajectory Safety Quantitative Performance Index Eliminating Probability Dilution. Science Chin Technological Sciences, 57(6), 1219–1228.Google Scholar
Vittaldev, V., Russell, R. P. and Linares, R. (2016). Spacecraft Uncertainty Propagation Using Gaussian Mixture Models and Polynomial Chaos Expansions. Journal of Guidnce, Control, and Dynamics, 39(12), 2615–2626.Google Scholar
Wang, Y., Bai, Y. Z., Ran, D. C., Zhao, Y., Zhang, X. and Chen, X. Q. (2017). The Equal-collision-probability-surface for Spacecraft Collision Avoidance. In: 3rd IAA Conference on Dynamics and Control of Space Systems, Moscow, IAA-AAS-DyCoss3-037.Google Scholar
Wang, Y., Bai, Y. Z., Xing, J. J., Gianmarco, R., Ni, Q., Chen, X. Q. (2018). Equal-collision-probability-curve method for Safe Spacecraft Close-range Proximity Maneuvers. Advance in Space Research, 2018. doi:10.1016/j.asr.2018.07.007.Google Scholar
Xing, J. J., Tang, G. J., Xi, X. N. and Li, H. Y. (2007). Satellite Formation Design and Optimal Stationkeeping Considering Nonlinearity and Eccentricity. Journal of Guidance, Control, and Dynamics, 30(5), 1523–1528.Google Scholar
Xing, J. J., Yu, Y., Wang, Y., Zheng, L. M. and Chen, Z. A. (2016). Robust Control of Low Earth Satellites Formation Based on Improved Linear Quadratic Regular. Journal of National University of Defense Technology, 38(3), 100–106. (in Chinese)Google Scholar
Yang, Z., Luo, Y. Z., Zhang, J. and Tang, G. J. (2016). Uncertainty Quantification Short Rendezvous Missions Using a Nonlinear Covariance Propagation Method. Journal of Guidance, Control, and Dynamics, 39(9), 2167–2175.Google Scholar
Yu, J., Chen, X. Q., and Chen, L. H. (2015). Optimal Planning of LEO Active Debris Removal based on Hybrid Optimal Control Theory. Advances in Space Research, 55(11), 2628–2640.Google Scholar