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L1 Penalized Sequential Convex Programming for Fast Trajectory Optimization: With Application to Optimal Missile Guidance

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Abstract

In this paper, an L1 penalized sequential convex programming (LPSCP) method for trajectory optimization is proposed. Sequential convex methods dramatically reduce computation time for nonlinear trajectory optimizations, based on the desirable properties of convex optimization algorithms. Due to its fast convergence speed, the sequential convex method is considered as a near-future candidate for real-time optimal online guidance. However, the generic sequential convex method seldom suffers from poor robustness to crude the initial trajectory estimates and constraint perturbations, which limits its application to real-world systems. Suggested LPSCP method resolves the robustness issue of generic sequential convex methods, by addressing the convex subproblem infeasibility. While improving its robustness, proposed LPSCP method maintains its fast convergence property. Consequently, LPSCP method enhances overall versatility of sequential convex method for trajectory optimization, which includes ameliorated robustness toward initial trajectory estimates, and improved stability to state and constraint perturbations. Throughout the paper, details of LPSCP method are outlined along with an application example to missile trajectory optimization problems. Desirable properties of LPSCP method are demonstrated through several simulated examples. Optimized trajectories are compared with results from the pseudospectral method. Numerical simulation and Monte Carlo analysis show that LPSCP method accelerates optimization process dramatically (−98.2% on average) while producing the same optimal trajectory.

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Acknowledgements

The authors inform that the paper is partially based on a pre-submitted master’s thesis [33] including some of optimization results.

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Authors and Affiliations

  1. Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea

    Heekun Roh, Young-Jae Oh & Min-Jea Tahk

  2. Agency for Defense Development (ADD), Daejeon, 34186, Republic of Korea

    Ki-Jeong Kwon

  3. LIG Nex1, Gyeonggi-do, 16911, Republic of Korea

    Hyuck-Hoon Kwon

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  1. Heekun Roh
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  2. Young-Jae Oh
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  3. Min-Jea Tahk
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  4. Ki-Jeong Kwon
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  5. Hyuck-Hoon Kwon
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Correspondence to Heekun Roh.

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Roh, H., Oh, YJ., Tahk, MJ. et al. L1 Penalized Sequential Convex Programming for Fast Trajectory Optimization: With Application to Optimal Missile Guidance. Int. J. Aeronaut. Space Sci. 21, 493–503 (2020). https://doi.org/10.1007/s42405-019-00230-0

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