Skip to main content
Log in

Optimal Control for a Cooperative Rendezvous Between Two Spacecraft from Determined Orbits

  • Technical Note
  • Published:
The Journal of the Astronautical Sciences Aims and scope Submit manuscript

Abstract

The mathematical model of a far-distance cooperative rendezvous between two spacecraft in a non-Keplerian orbit was established. Approximate global optimization was performed by a type of hybrid algorithm consisting of particle swarm optimization and differential evolution. In this process, the double-fitness function was established according to the objective function and the constraints; the double-fitness function was used to enable a better choice between the solutions obtained by the two algorithms at every iteration. In addition, the costate variables obtained were set as the initial values of the sequential quadratic programming to greatly increase the possibility of finding the approximate global optimal solution. After performing the calculations and simulations, it was concluded that the fuel required for orbiting was not influenced by the initial positions of the two spacecraft if the initial orbits of the two spacecraft were determined. However, the time consumption is strongly influenced in this situation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Abbreviations

a :

semimajor axis

e :

eccentricity

i :

orbit inclination angle

I sp :

thruster-specific impulse

J :

performance index

m 0 :

initial mass of the satellite

R e :

equator radius

u :

ratio of the amplitude of the actual thrust relative to T max

α :

unit direction vector

β :

pitch angle

θ :

true anomaly

Φ :

shooting equation

γ :

yaw angle

λ :

costate

μ :

gravitational constant of the earth

ω :

perigee amplitude

Ω:

longitude ascending node

References

  1. Massioni, P., Keviczky, T., Gill, E., Verhaegen, M.: A Decomposition-Based Approach to Linear Time-Periodic Distributed Control of satellite Formations [J]. IEEE Trans. Control. Syst. Technol. 19(3), 481–492 (2011)

    Article  Google Scholar 

  2. Jingrui, Z., Shuge, Z., Yongzhao, Y.: Characteristics Analysis for Elliptical Orbit Hovering Based on Relative Dynamics [J]. IEEE Trans. Aerosp. Electron. Syst. 49(4), 2742–2750 (2013)

    Article  Google Scholar 

  3. Vinh, N.X., Lu, P., Howe, R.M., Gilbert, E.G.: Optimal interception with time constraint [J]. J. Optim. Theory Appl. 66(3), 361–390 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  4. Renzhang, Z.: Rendezvous and Docking Techniques of Spacecraft[M], p 10. National Defense Industry Press, Beijing (2007)

    Google Scholar 

  5. Prussing, J.E.: A Class of optimal tow-impulse rendezvous using multiple-revolution Lambert solutions [J]. J. Astronaut. Sci. 48(2-3), 131–148 (2000)

    Google Scholar 

  6. Carter, T., Humi, M.: A new approach to impulsive rendezvous near circular orbit [J]. Celest. Mech. Dyn. Astron. 112(4), 385–426 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  7. Tang, G.J., Luo, Y.Z., Li, H.Y.: Optimal robust linearized impulsive rendezvous [J]. Aerosp. Sci. Technol. 11(7-8), 563–569 (2007)

    Article  MATH  Google Scholar 

  8. dos Santos, D.P.S., de Almeida Prado, A.F.B., Colasurdo, G.: Four-impulsive rendezvous maneuvers for spacecrafts in circular orbits using genetic algorithms [J]. Math. Probl. Eng. 2012(493507), 16 (2012)

    Google Scholar 

  9. Coverstone-Carroll, V., Prussing, J.E.: Optimal cooperative power-limited rendezvous between neighboring circular orbits [J]. J. Guid. Control. Dyn. 16(6), 1045–1054 (1993)

    Article  MATH  Google Scholar 

  10. Coverstone-Carroll, V., Prussing, J.E.: Optimal cooperative power-limited rendezvous between coplanar circular orbits [J]. J. Guid. Control. Dyn. 17(5), 1096–1102 (1994)

    Article  MATH  Google Scholar 

  11. Crispin, Y., Seo, D.: Rendezvous between two active spacecraft with continuous low thrust [M]. Advances in Spacecraft Technologies, 585–596 (2011)

  12. Dutta, A., Tsiotras, P.: Hohmann-Hohmann and Hohmann-phasing cooperative rendezvous maneuvers [J]. J. Astronaut. Sci. 57(1-2), 393–417 (2009)

    Article  Google Scholar 

  13. Bertrand, R., Epenoy, R.: New smoothing techniques for solving bang–bang optimal control problems—numerical results and statistical interpretation [J]. Optimal Control Applications and Methods 23(4), 171–197 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  14. Sun, L., Huo, W.: Robust adaptive control for spacecraft cooperative rendezvous and docking[C]. In: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, pp 5516–5521 (2013)

  15. Kennedy, J., Eberhart, R.: Particle swarm optimization [C]. In: Proceedings of IEEE International Conference on Neural Networks, pp 1942–1948. Piscataway, NJ (1995)

    Chapter  Google Scholar 

  16. Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory [C]. In: Proceedings of the International Symposium on Micro Machine and Human Science, Piscataway, NJ, USA: IEEE, pp 39–43 (1995)

  17. Pontani, M., Conway, B.A.: Particle swarm optimization applied to space trajectories [J]. J. Guid. Control. Dyn. 33(5), 1429–1441 (2010)

    Article  Google Scholar 

  18. Pontani, M., Ghosh, P., Conway, B.A.: Particle swarm optimization of multiple-burn rendezvous trajectories [J]. J. Guid. Control. Dyn. 35(4), 1192–1207 (2012)

    Article  Google Scholar 

  19. Price, K.V.: Differential evolution: a fast and simple numerical optimizer [C] (1996)

  20. Storn, R., Price, K.: Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces [J]. J. Glob. Optim. 11(4), 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  21. Olds, A.D., Kluever, C.A., Cupples, ML.: Interplanetary mission design using differential evolution [J]. J. Spacecr. Rocket. 44(5), 1060–1070 (2007)

    Article  Google Scholar 

  22. Das, S., Abraham, A., Konar, A.: Particle swarm optimization and differential evolution algorithms: technical analysis, applications and hybridization perspectives [M]. Advances of Computational Intelligence in Industrial Systems. In: Liu, Y., et al. (eds.) Studies in Computational Intelligence, pp 1–34. Springer, Germany (2008)

    Google Scholar 

  23. Zhang, C., Ning, J., Lu, S., et al.: A novel hybrid differential evolution and particle swarm optimization algorithm for unconstrained optimization [J]. Oper. Res. Lett. 37(2), 117–122 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  24. Liu, H., Cai, Z., Wang, Y.: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization [J]. Appl. Soft Comput. 10(2), 629–640 (2010)

    Article  Google Scholar 

  25. Powell, D., Skolnick, M.: Using genetic algorithms in engineering design optimization with nonlinear constraints [C] (1993)

  26. Kim, Y.H., Spencer, D.B.: Optimal spacecraft rendezvous using genetic algorithms [J]. J. Spacecr. Rocket. 39(6), 859–865 (2002)

    Article  Google Scholar 

  27. Luo, Y.Z., Tang, G.J., Li, H.: Optimization of multiple-impulse minimum-time rendezvous with impulse constraints using a hybrid genetic algorithm[J]. Aerosp. Sci. Technol. 10(6), 534–540 (2006)

    Article  MATH  Google Scholar 

  28. Dos Santos, D.P.S., Prado, A F.B.A.: Minimum Fuel Multi-Impulsive Orbital Mane

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Weiming Feng.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Feng, W., Han, L., Shi, L. et al. Optimal Control for a Cooperative Rendezvous Between Two Spacecraft from Determined Orbits. J of Astronaut Sci 63, 23–46 (2016). https://doi.org/10.1007/s40295-015-0079-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40295-015-0079-4

Keywords

Navigation