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Review Article

Survey of convex optimization for aerospace applications

Xinfu Liu1(), Ping Lu2, Binfeng Pan3
Beijing Institute of Technology, Beijing 100081, China
San Diego State University, San Diego, California 92182-1308, USA
Northwestern Polytechnical University, Xi’an 710072, China
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Abstract

Convex optimization is a class of mathematical programming problems with polynomial complexity for which state-of-the-art, highly efficient numerical algorithms with pre-determinable computational bounds exist. Computational efficiency and tractability in aerospace engineering, especially in guidance, navigation, and control (GN&C), are of paramount importance. With theoretical guarantees on solutions and computational efficiency, convex optimization lends itself as a very appealing tool. Coinciding the strong drive toward autonomous operations of aerospace vehicles, convex optimization has seen rapidly increasing utility in solving aerospace GN&C problems with the potential for onboard real-time applications. This paper attempts to provide an overview on the problems to date in aerospace guidance, path planning, and control where convex optimization has been applied. Various convexification techniques are reviewed that have been used to convexify the originally nonconvex aerospace problems. Discussions on how to ensure the validity of the convexification process are provided. Some related implementation issues will be introduced as well.

Keywords

convex optimizationoptimal controlconvexificationconvex relaxation

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Astrodynamics
Volume 1 Issue 1,
September 2017
Pages 23-40
DOI: 10.1007/s42064-017-0003-8
Cite this article:
Liu X, Lu P, Pan B. Survey of convex optimization for aerospace applications. Astrodynamics, 2017, 1(1): 23-40. https://doi.org/10.1007/s42064-017-0003-8
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