Evolutionary Trajectory Optimization for Suborbital Spaceplane by Combining Direct and Inverse Trajectory Design Approach

Author:

Murakami Masaaki,Fujikawa Takahiro,Yonemoto Koichi

Publisher

Springer Nature Singapore

Reference10 articles.

1. Chai, R., Savvaris, A., Tsourdos, A., Xia, Y., Chai, S.: Solving multi-objective constrained trajectory optimization problem by an extended evolutionary algorithm. IEEE Trans. Cybern. 50, 1630–1643 (2020)

2. Yokoyama, N., Suzuki, S.: Modified genetic algorithm for constrained trajectory optimization. J. Guid. Control. Dyn. 28(1), 139–144 (2005)

3. Miyamoto, S., Matsumoto, T., Yonemoto, K.: Dynamically distributed genetic algorithm and its application to diversely selectable trajectory optimization of winged rockets. Trans. Jpn. Soc. Aeronaut. Space Sci. Aerosp. Technol. Jpn. 12, 37–46 (2014)

4. Koshida, Y.: Optimal return trajectory generation and guidance law for suborbital spaceplane considering command continuity. Master’s thesis, Tokyo University of Science (2022)

5. Fujikawa, T., Yonemoto, K.: Comparison of deterministic and stochastic global optimization methods for real-time generation of guidance trajectories. In: Lee, S., Han, C., Choi, J.-Y., Kim, S., Kim, J.H. (eds.) APISAT 2021, pp. 1003–1019. Springer, Singapore (2023). https://doi.org/10.1007/978-981-19-2635-8_74

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