Improved time-optimal static programming algorithm for hypersonic vehicle

References

• An, H., Liu, J., Wang, C., & Wu, L. (2016). Disturbance observer-based antiwindup control for air-breathing hypersonic vehicles. IEEE Transactions on Industrial Electronics, 63(5), 3038–3049. https://doi.org/10.1109/TIE.2016.2516498
   Web of Science ®Google Scholar
• An, P. T., Hai, N. N., & Hoai, T. V. (2013). Direct multiple shooting method for solving approximate shortest path problems. Journal of Computational and Applied Mathematics, 244, 67–76. https://doi.org/10.1016/j.cam.2012.11.001
   Web of Science ®Google Scholar
• Antony, T., & Grant, M. J. (2017). Rapid indirect trajectory optimization on highly parallel computing architectures. Journal of Spacecraft and Rockets, 54(5), 1081–1091. https://doi.org/10.2514/1.A33755
   Web of Science ®Google Scholar
• Betts, J. T. (1998). Survey of numerical methods for trajectory optimization. Journal Of Guidance, Control, and Dynamics, 21(2), 193–207. https://doi.org/10.2514/2.4231
   Web of Science ®Google Scholar
• Betts, J. T., Campbell, S., & Digirolamo, C. (2021). Examination of solving optimal control problems with delays using GPOPS-II. Numerical Algebra, Control & Optimization, 11(2), 283. https://doi.org/10.3934/naco.2020026
   Google Scholar
• Bryson, A. E., & Ho, Y. C. (2018). Applied optimal control: Optimization, estimation, and control. Routledge.
   Google Scholar
• Chai, R., Tsourdos, A., Savvaris, A., Wang, S., Xia, Y., & Chai, S. (2020). Fast generation of chance-constrained flight trajectory for unmanned vehicles. IEEE Transactions on Aerospace and Electronic Systems, 57(2), 1028–1045. https://doi.org/10.1109/TAES.2020.3037417
   Web of Science ®Google Scholar
• Chen, K. J., & Zhao, H. Y. (1994). An optimal reentry maneuver guidance law applying to attack the ground fixed target. Journal of Astronautics, 15(1), 1–7.
   Google Scholar
• Chu, H., Li, J., Dong, Y., Yang, X., & Tao, Y. (2017). Improved MPSP method-based cooperative re-entry guidance for hypersonic gliding vehicles. In Matec web of conferences (Vol. 114, p. 01002). EDP Sciences.
   Google Scholar
• Conway, B. A. (2012). A survey of methods available for the numerical optimization of continuous dynamic systems. Journal of Optimization Theory and Applications, 152(2), 271–306. https://doi.org/10.1007/s10957-011-9918-z
   Web of Science ®Google Scholar
• Duan, H., Liu, S., & Wu, J. (2009). Novel intelligent water drops optimization approach to single UCAV smooth trajectory planning. Aerospace Science and Technology, 13(8), 442–449. https://doi.org/10.1016/j.ast.2009.07.002
   Web of Science ®Google Scholar
• Fu, B., Guo, H., Chen, K., Fu, W., & Yan, J. (2018). Aero-thermal heating constrained midcourse guidance using state-constrained model predictive static programming method. Journal of Systems Engineering and Electronics, 29(6), 1263–1270. https://doi.org/10.21629/JSEE.2018.06.13
   Web of Science ®Google Scholar
• Grimm, W., van der Meulen, J. G., & Roenneke, A. J. (2003). Update scheme for drag reference profiles in an entry guidance. Journal Of Guidance, Control, and Dynamics, 26(5), 695–701. https://doi.org/10.2514/2.5123
   Web of Science ®Google Scholar
• Guelman, M. (1976). The closed-form solution of true proportional navigation. IEEE Transactions on Aerospace and Electronic Systems, AES-12(4), 472–482. https://doi.org/10.1109/TAES.1976.308328
   Web of Science ®Google Scholar
• Hagiwara, T., Yuasa, T., & Araki, M. (1993). Stability of the limiting zeros of sampled-data systems with zero-and first-order holds. International Journal of Control, 58(6), 1325–1346. https://doi.org/10.1080/00207179308923057
   Web of Science ®Google Scholar
• Herrera, I., & DIaz, M. (1999). Indirect methods of collocation: Trefftz–Herrera collocation. Numerical Methods for Partial Differential Equations: An International Journal, 15(6), 709–738. https://doi.org/10.1002/(SICI)1098-2426(199911)15:6<709::AID-NUM7>3.0.CO;2-X
   Web of Science ®Google Scholar
• Kayama, Y., Howell, K. C., Bando, M., & Hokamoto, S. (2022). Low-thrust trajectory design with successive convex optimization for libration point orbits. Journal of Guidance, Control, and Dynamics, 45(4), 623–637. https://doi.org/10.2514/1.G005916
   Web of Science ®Google Scholar
• Kelly, M. (2017). An introduction to trajectory optimization: How to do your own direct collocation. SIAM Review, 59(4), 849–904. https://doi.org/10.1137/16M1062569
   Web of Science ®Google Scholar
• Kumar, P., Anoohya, B. B., & Padhi, R. (2019). Model predictive static programming for optimal command tracking: A fast model predictive control paradigm. Journal of Dynamic Systems, Measurement, and Control, 141(2), 021014. https://doi.org/10.1115/1.4041356
   Web of Science ®Google Scholar
• Li, Y., Aghvami, A. H., & Dong, D. (2021). Intelligent trajectory planning in UAV-mounted wireless networks: A quantum-inspired reinforcement learning perspective. IEEE Wireless Communications Letters, 10(9), 1994–1998. https://doi.org/10.1109/LWC.2021.3089876
   Web of Science ®Google Scholar
• Lu, C., Feng, Y. W., Liem, R. P., & Fei, C. W. (2018). Improved Kriging with extremum response surface method for structural dynamic reliability and sensitivity analyses. Aerospace Science and Technology, 76, 164–175. https://doi.org/10.1016/j.ast.2018.02.012
   Web of Science ®Google Scholar
• Lu, P., Doman, D. B., & Schierman, J. D. (2006). Adaptive terminal guidance for hypervelocity impact in specified direction. Journal Of Guidance, Control, and Dynamics, 29(2), 269–278. https://doi.org/10.2514/1.14367
   Web of Science ®Google Scholar
• Malyuta, D., Reynolds, T., Szmuk, M., Mesbahi, M., Acikmese, B., & Carson, J. M. (2019). Discretization performance and accuracy analysis for the rocket powered descent guidance problem. In AIAA scitech 2019 forum (p. 0925).
   Google Scholar
• Mattingley, J., & Boyd, S. (2012). CVXGEN: A code generator for embedded convex optimization. Optimization and Engineering, 13(1), 1–27. https://doi.org/10.1007/s11081-011-9176-9
   Web of Science ®Google Scholar
• Padhi, R., & Kothari, M. (2009). Model predictive static programming: A computationally efficient technique for suboptimal control design. International Journal of Innovative Computing Information and Control, 5(2), 399–411.
   Web of Science ®Google Scholar
• Patterson, M. A., & Rao, A. V. (2014). GPOPS-II: A MATLAB software for solving multiple-phase optimal control problems using hp-adaptive Gaussian quadrature collocation methods and sparse nonlinear programming. ACM Transactions on Mathematical Software (TOMS, 41(1), 1–37. https://doi.org/10.1145/2558904
   Web of Science ®Google Scholar
• Reddy, S. S., & Panigrahi, B. K. (2017). Fuzzified multi-objective particle swarm optimisation for the solution of economic and emission dispatch problem. International Journal of Power and Energy Conversion, 8(3), 276–294. https://doi.org/10.1504/IJPEC.2017.084916
   Google Scholar
• Salkuti, S. R. (2020). Optimal short-term hydro-thermal scheduling using multi-function global particle swarm optimization. Indonesian Journal of Electrical Engineering and Computer Science, 20(1), 537–544. https://doi.org/10.11591/ijeecs.v20.i1.pp537-544
   Google Scholar
• Sun, H., Li, S., & Sun, C. (2013). Finite time integral sliding mode control of hypersonic vehicles. Nonlinear Dynamics, 73(1), 229–244. https://doi.org/10.1007/s11071-013-0780-4
   Web of Science ®Google Scholar
• Wang, Y., & Topputo, F. (2020). Robust bang-off-bang low-thrust guidance using model predictive static programming. Acta Astronautica, 176, 357–370. https://doi.org/10.1016/j.actaastro.2020.06.037
   Web of Science ®Google Scholar
• Wang, Z., & Grant, M. J. (2017). Constrained trajectory optimization for planetary entry via sequential convex programming. Journal of Guidance, Control, and Dynamics, 40(10), 2603–2615. https://doi.org/10.2514/1.G002150
   Web of Science ®Google Scholar
• Wang, Z., & Lu, Y. (2020). Improved sequential convex programming algorithms for entry trajectory optimization. Journal of Spacecraft and Rockets, 57(6), 1373–1386. https://doi.org/10.2514/1.A34640
   Web of Science ®Google Scholar
• Wong, W. K., & Zhou, J. (2019). CVX-based algorithms for constructing various optimal regression designs. Canadian Journal of Statistics, 47(3), 374–391. https://doi.org/10.1002/cjs.11499
   Web of Science ®Google Scholar
• Xiong, X., Min, H., Yu, Y., & Wang, P. (2021). Application improvement of A* algorithm in intelligent vehicle trajectory planning. Mathematical Biosciences and Engineering, 18(1), 1–21. https://doi.org/10.3934/mbe.2021001
   Web of Science ®Google Scholar
• Xu, X., Li, Y., Yang, Y., & Xu, H. (2016). A method of trajectory planning for Ground Mobile Robot based on ant colony algorithm. In 2016 IEEE international conference on robotics and biomimetics (ROBIO) (pp. 2117–2121). IEEE.
   Google Scholar
• Xue, S., & Lu, P. (2010). Constrained predictor-corrector entry guidance. Journal of Guidance, Control, and Dynamics, 33(4), 1273–1281. https://doi.org/10.2514/1.49557
   Web of Science ®Google Scholar
• Yen, V. (1995). An inverse dynamic-based dynamic programming method for optimal point-to-point trajectory planning of robotic manipulators. International Journal of Systems Science, 26(2), 181–195. https://doi.org/10.1080/00207729508929030
   Web of Science ®Google Scholar
• Yu, C. M., Zhao, D. J., & Yang, Y. (2019). Efficient convex optimization of reentry trajectory via the chebyshev pseudospectral method. International Journal of Aerospace Engineering, 2019. https://doi.org/10.1155/2019/1414279
   Web of Science ®Google Scholar
• Zhang, Z., Wu, J., Dai, J., & He, C. (2020). Rapid penetration path planning method for stealth uav in complex environment with bb threats. International Journal of Aerospace Engineering, 2020. https://doi.org/10.1155/2020/8896357
   Web of Science ®Google Scholar