Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Trajectory optimization for RLV in TAEM phase using adaptive Gauss pseudospectral method

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

References

  1. 1

    Horneman K, Kluever C. Terminal area energy management trajectory planning for an unpowered reusable launch vehicle. In: Proceedings of AIAA Atmospheric Flight Mechanics Conference and Exhibit, 2004. 5183

  2. 2

    Kluever C, Horneman K. Terminal trajectory planning and optimization for an unpowered reusable launch vehicle. In: Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit, 2005. 6058

  3. 3

    de Ridder S, Mooij E. Terminal area trajectory planning using the energy-tube concept for reusable launch vehicles. Acta Astronaut, 2011, 68: 915–930

  4. 4

    Mu L X, Yu X, Zhang Y M, et al. Onboard guidance system design for reusable launch vehicles in the terminal area energy management phase. Acta Astronaut, 2018, 143: 62–75

  5. 5

    Guo L L, Gao B Z, Li Y, et al. A fast algorithm for nonlinear model predictive control applied to HEV energy management systems. Sci China Inf Sci, 2017, 60: 092201

  6. 6

    Tian B L, Fan W R, Su R, et al. Real-time trajectory and attitude coordination control for reusable launch vehicle in reentry phase. IEEE Trans Ind Electron, 2015, 62: 1639–1650

Download references

Acknowledgements

This work was supported by China Postdoctoral Science Foundation (Grant No. 2017M620858). The authors would like to greatly appreciate the editor and all the anonymous reviewers for their comments, which helped to improve the quality of this letter.

Author information

Correspondence to Chaofan Zhang.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dong, Q., Zhang, C. Trajectory optimization for RLV in TAEM phase using adaptive Gauss pseudospectral method. Sci. China Inf. Sci. 62, 10206 (2019). https://doi.org/10.1007/s11432-018-9547-4

Download citation