The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Model Predictive Control approach for guidance of spacecraft rendezvous and proximity maneuvering
Abstract
SUMMARY: Traditionally, rendezvous and proximity maneuvers have been performed using open‐loop maneuver planning techniques and ad hoc error corrections. In this paper, a Model Predictive Control (MPC) approach is applied to spacecraft rendezvous and proximity maneuvering problems in the orbital plane. We demonstrate that various constraints arising in these maneuvers can be effectively handled with the MPC approach. These include constraints on thrust magnitude, constraints on spacecraft positioning within Line‐of‐Sight cone while approaching the docking port on a target platform, and constraints on approach velocity to match the velocity of the docking port. The two cases of a nonrotating and a rotating (tumbling) platform are treated separately, and trajectories are evaluated in terms of maneuver time and fuel consumption. For the case when the platform is not rotating and the docking port position is fixed with respect to the chosen frame, an explicit offline solution of the MPC optimization problem is shown to be possible; this explicit solution has a form of a piecewise affine control law suitable for online implementation without an on‐board optimizer. In the case of a fast rotating platform, it is, however, shown that the prediction of the platform rotation is necessary to successfully accomplish the maneuvers and to reduce fuel consumption. Finally, the proposed approach is applied to debris avoidance maneuvers with the debris in the spacecraft rendezvous path. The significance of this paper is in demonstrating that Model Predictive Control can be an effective feedback control approach to satisfy various maneuver requirements, reduce fuel consumption, and provide robustness to disturbances. Copyright © 2012 John Wiley & Sons, Ltd.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
(2021) · A First Course in Statistical Programming with R · doi:10.1017/9781108993456.011 · Cited by 13,724
(2006) · Springer Series in Operations Research and Financial Engineering · doi:10.1007/978-0-387-40065-5 · Cited by 9,008
Constrained model predictive control: Stability and optimality
Mayne, D. Q., Rawlings, J. B., Rao, C. V., & Scokaert, P. O. M. (2000) · Automatica · doi:10.1016/s0005-1098(99)00214-9 · Cited by 8,736
Predictive Control With Constraints
Maciejowski, J. M. (2001) · Cambridge University Engineering Department Publications Database · Cited by 4,368
Generalized predictive control—Part I. The basic algorithm
Clarke, D. W., Mohtadi, C., & Tuffs, P. S. (1987) · Automatica · doi:10.1016/0005-1098(87)90087-2 · Cited by 3,799
The explicit linear quadratic regulator for constrained systems
Bemporad, A., Morari, M., Dua, V., & Pistikopoulos, E. N. (2002) · Automatica · doi:10.1016/s0005-1098(01)00174-1 · Cited by 3,260
Robust constrained model predictive control using linear matrix inequalities
Kothare, M. V., Balakrishnan, V., & Morari, M. (1996) · Automatica · doi:10.1016/0005-1098(96)00063-5 · Cited by 2,516
Terminal Guidance System for Satellite Rendezvous
CLOHESSY, W. H., & WILTSHIRE, R. S. (1960) · Journal of the Aerospace Sciences · doi:10.2514/8.8704 · Cited by 2,084
Robust model predictive control of constrained linear systems with bounded disturbances
Mayne, D. Q., Seron, M. M., & Raković, S. V. (2005) · Automatica · doi:10.1016/j.automatica.2004.08.019 · Cited by 1,672
Metadata
- Authors
- Di Cairano, S., Park, H., & Kolmanovsky, I.
- Venue
- International Journal of Robust and Nonlinear Control
- Publisher
- Wiley
- Published
- 2012-05-15
- Volume
- 22
- Issue
- 12
- Pages
- 1398-1427
- ISSN
- 1049-8923 (ISSN-L)
- 1099-1239
- OpenAlex
- W1528431624
- Cited by
- 273
- References
- 29
- FWCI
- 17.14
- Type
- journal article
- Language
- en
- Open access
- closed
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