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Practical Applications of Intelligent Systems pp 147–156Cite as

Modified Quasilinearization Method for Optimal Launch Mission Planning Problems

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 124))

Abstract

Optimal launch mission planning is one of the most important engineering fields where optimization tools and optimal control theory have found routine application. Optimal control theory is critical for launch mission to meet mission requirement such as minimum time, minimum fuel requirement, minimizing undershooting and so on. Compared to traditional off-line launch mission planning, on-line launch mission planning could generate guidance plan with respect to the current situation of the vehicles to enhance the guidance precision greatly and reduce the risks resulted by unpredictable events, while the core issue of on-board launch mission planning is how to solve the corresponding Two-Point Boundary-Value Problem (TPBVP) quickly, efficiently and precisely. We intend to introduce a stable algorithm here with a verified convergent ability to handle optimal launch mission planning problems with relatively little time consumption.

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Author information

Authors and Affiliations

  1. Institute of Aerospace Science & Technology, Shanghai Jiao Tong University, Aerospace Building,800 Dongchuan Rd., Shanghai, 200240, P.R.China

    Zhongjie Lin, Yongsheng Yang & Zhongliang Jin

Authors
  1. Zhongjie Lin
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  2. Yongsheng Yang
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  3. Zhongliang Jin
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Yinglin Wang

  2. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, Sichuan Province, China

    Tianrui Li

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© 2011 Springer-Verlag Berlin Heidelberg

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Lin, Z., Yang, Y., Jin, Z. (2011). Modified Quasilinearization Method for Optimal Launch Mission Planning Problems. In: Wang, Y., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25658-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-25658-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25657-8

  • Online ISBN: 978-3-642-25658-5

  • eBook Packages: EngineeringEngineering (R0)

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