ACTA AERONAUTICAET ASTRONAUTICA SINICA >
High-precision adaptive convex programming for reentry trajectories of suborbital vehicles
Received date: 2023-08-10
Revised date: 2023-08-11
Accepted date: 2023-09-13
Online published: 2023-09-27
Supported by
National Natural Science Foundation of China(52232014);1912 Project
Under complete terminal state constraints, the reentry gliding trajectory planning of suborbital reusable aircraft is short of convergence and accuracy. A high-precision solution algorithm combining sequential convex optimization and adaptive mesh refinement based homotopic constrained model predictive convex programming is proposed to achieve high-precision and reliable convergence in the reentry trajectory planning process under the conditions of weak initial value dependency. Firstly, several terminal constraints are relaxed, and the trust region is utilized as a soft constraint during the convex optimization process. An augmented index function is defined to reflect the linearization error and the degree of constraint violation. A multi-dimensional parameter search method is proposed to update the state and control variables separately, avoiding the situation of no solution in the basic line search. Further, constraint relaxation terms are selected as homotopy parameters, the discrete mesh is adjusted adaptively based on evaluation of model prediction deviation, and a static convex programming problem model is constructed considering multi-constraints. Then, the control adjustment quantity in the entire process is homotopically optimized to achieve high-precision correction of all-element trajectory state variables and improve algorithm convergence. Finally, the effectiveness of the proposed method is verified through numerical simulation.
Zhe LIU , Xige ZHANG , Changzhu WEI , Naigang CUI . High-precision adaptive convex programming for reentry trajectories of suborbital vehicles[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(S2) : 729430 -729430 . DOI: 10.7527/S1000-6893.2023.29430
| 1 | SIPPEL M， STAPPERT S， KOCH A. Assessment of multiple mission reusable launch vehicles［J］. Journal of Space Safety Engineering， 2019， 6（3）： 165-180. |
| 2 | 包为民， 汪小卫. 航班化航天运输系统发展展望［J］. 宇航总体技术， 2021， 5（3）： 1-6. |
| BAO W M， WANG X W. Prospect of airline-flight-mode aerospace transportation system［J］. Astronautical Systems Engineering Technology， 2021， 5（3）： 1-6 （in Chinese）. | |
| 3 | PAN L， PENG S C， XIE Y， et al. 3D guidance for hypersonic reentry gliders based on analytical prediction［J］. Acta Astronautica， 2020， 167： 42-51. |
| 4 | 张柔和， 樊雅卓， 佘智勇， 等. TSTO运载器一级返场轨迹优化设计与在线生成［J］. 航空学报， 2020， 41（11）： 623856. |
| ZHANG R H， FAN Y Z， SHE Z Y， et al. TSTO vehicle first-stage return trajectory： Optimization and onboard generation［J］. Acta Aeronautica et Astronautica Sinica， 2020， 41（11）： 623856 （in Chinese）. | |
| 5 | MALL K， TAHERI E. Three-degree-of-freedom hypersonic reentry trajectory optimization using an advanced indirect method［J］. Journal of Spacecraft and Rockets， 2022， 59（5）： 1463-1474. |
| 6 | SU Y， DAI Y， LIU Y. A hybrid hyper-heuristic whale optimization algorithm for reusable launch vehicle reentry trajectory optimization［J］. Aerospace Science and Technology， 2021， 119： 107200. |
| 7 | LI Z T， TANG X J， ZHANG H B， et al. A fast matrix generation method for solving entry trajectory optimization problems under the pseudospectral method［J］. Proceedings of the Institution of Mechanical Engineers， Part G： Journal of Aerospace Engineering， 2022， 236（12）： 2565-2579. |
| 8 | LIU X F， SHEN Z J， LU P. Solving the maximum-crossrange problem via successive second-order cone programming with a line search［J］. Aerospace Science and Technology， 2015， 47： 10-20. |
| 9 | WANG Z B， MCDONALD S T. Convex relaxation for optimal rendezvous of unmanned aerial and ground vehicles［J］. Aerospace Science and Technology， 2020， 99： 105756. |
| 10 | WANG Z B. Optimal trajectories and normal load analysis of hypersonic glide vehicles via convex optimization［J］. Aerospace Science and Technology， 2019， 87： 357-368. |
| 11 | WANG Z B， LU Y. Improved sequential convex programming algorithms for entry trajectory optimization［J］. Journal of Spacecraft and Rockets， 2020， 57（6）： 1373-1386. |
| 12 | GAO Y， SHAO Z J， SONG Z Y. Enhanced successive convexification based on error-feedback index and line search filter［J］. Journal of Guidance， Control， and Dynamics， 2022， 45（12）： 2243-2257. |
| 13 | LU P. Convex-concave decomposition of nonlinear equality constraints in optimal control［J］. Journal of Guidance， Control， and Dynamics， 2021， 44（1）： 4-14. |
| 14 | REYNOLDS T P， MESBAHI M. The crawling phenomenon in sequential convex programming［C］∥ 2020 American Control Conference （ACC）. Piscataway： IEEE Press， 2020： 3613-3618. |
| 15 | XIE L， HE R Z， ZHANG H B， et al. Oscillation phenomenon in trust-region-based sequential convex programming for the nonlinear trajectory planning problem［J］. IEEE Transactions on Aerospace and Electronic Systems， 2022， 58（4）： 3337-3352. |
| 16 | VUTUKURI S， PADHI R. An impulsive model predictive static programming based station-keeping guidance for quasi-halo orbits［J］. Acta Astronautica， 2021， 188： 518-530. |
| 17 | ZHOU C， HE L， YAN X D， et al. Active-set pseudospectral model predictive static programming for midcourse guidance［J］. Aerospace Science and Technology， 2023， 134： 108137. |
| 18 | LIU X， LI S， XIN M. Pseudospectral convex optimization based model predictive static programming for constrained guidance［J］. IEEE Transactions on Aerospace and Electronic Systems， 2023， 59（3）： 2232-2244. |
| 19 | MONDAL S， PADHI R. Angle-constrained terminal guidance using quasi-spectral model predictive static programming［J］. Journal of Guidance， Control， and Dynamics， 2018， 41（3）： 783-791. |
| 20 | ZHOU C， YAN X D， TANG S. Generalized quasi-spectral model predictive static programming method using Gaussian quadrature collocation［J］. Aerospace Science and Technology， 2020， 106： 106134. |
| 21 | SHARMA P， KUMAR P， PADHI R. Pseudo-spectral MPSP-based unified midcourse and terminal guidance for reentry targets［J］. IEEE Transactions on Aerospace and Electronic Systems， 2023， 59（4）： 3982-3994. |
| 22 | HONG H C， MAITY A， HOLZAPFEL F， et al. Model predictive convex programming for constrained vehicle guidance［J］. IEEE Transactions on Aerospace and Electronic Systems， 2019， 55（5）： 2487-2500. |
| 23 | 周聪， 闫晓东， 唐硕， 等. 大气层内模型预测静态规划拦截中制导［J］. 航空学报， 2021， 42（11）： 524912. |
| ZHOU C， YAN X D， TANG S， et al. Midcourse guidance for endo-atmospheric interception based on model predictive static programming［J］. Acta Aeronautica et Astronautica Sinica， 2021， 42（11）： 524912 （in Chinese）. | |
| 24 | PASHUPATHY P， MAITY A， HONG H C， et al. Unspecified final-time nonlinear suboptimal guidance of aerobatic aircraft in air race［J］. Aerospace Science and Technology， 2021， 116： 106817. |
| 25 | MONDAL S， PADHI R. Constrained quasi-spectral MPSP with application to high-precision missile guidance with path constraints［J］. Journal of Dynamic Systems， Measurement， and Control， 2021， 143（3）： 031001. |
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