Developed Time-Optimal Model Predictive Static Programming Method with Fish Swarm Optimization for Near-Space Vehicle

To establish the optimal reference trajectory for a near-space vehicle under free terminal time, a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization. First, the model predictive static programming method is developed by incorporating neighborin...

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Bibliographic Details
Published in:Computer modeling in engineering & sciences Vol. 143; no. 2; pp. 1463 - 1484
Main Authors: Wang, Yuanzhuo, Dai, Honghua
Format: Journal Article
Language:English
Published: Henderson Tech Science Press 2025
Subjects:
Accuracy
Convergence
Dynamic programming
Energy consumption
Fish
Linear programming
Methods
Optimization techniques
Programming
Space vehicles
Trajectory optimization
Unmanned aerial vehicles
Vehicles
ISSN:1526-1506, 1526-1492, 1526-1506
Online Access:Get full text
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Summary:To establish the optimal reference trajectory for a near-space vehicle under free terminal time, a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization. First, the model predictive static programming method is developed by incorporating neighboring terms and trust region, enabling rapid generation of precise optimal solutions. Next, an adaptive fish swarm optimization technique is employed to identify a sub-optimal solution, while a momentum gradient descent method with learning rate decay ensures the convergence to the global optimal solution. To validate the feasibility and accuracy of the proposed method, a near-space vehicle example is analyzed and simulated during its glide phase. The simulation results demonstrate that the proposed method aligns with theoretical derivations and outperforms existing methods in terms of convergence speed and accuracy. Therefore, the proposed method offers significant practical value for solving the fast trajectory optimization problem in near-space vehicle applications.
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ISSN:1526-1506
1526-1492
1526-1506
DOI:10.32604/cmes.2025.064416