Author:
Marchetti Francesco,Minisci Edmondo,Riccardi Annalisa
Abstract
AbstractIn this paper, the ascent trajectory optimization of a lifting body Single-Stage To Orbit (SSTO) reusable launch vehicle is investigated. The work is carried out using a Direct Multiple Shooting method to solve the Optimal Control problem. The crucial initialisation of the optimisation process is performed by using a combination of two evolutionary algorithms, namely a Multi-Objective Parzen-based Estimation of Distribution (MOPED) algorithm and a Multi-Population Adaptive Inflationary Differential Evolution Algorithm (MP-AIDEA). Multi-Objective Parzen-based Estimation of Distribution (MOPED) belongs to the class of Estimation of Distribution Algorithms (EDAs) and it is used in the first phase of the initial guess research to explore the search space, then Multi-Population Adaptive Inflationary Differential Evolution Algorithm (MP-AIDEA) is used to refine the obtained results, and better fulfill the imposed constraints. The initial guesses obtained with this evolutionary framework were tested on different multiple shooting configurations. The importance of the continuity properties of the employed mathematical models was also quantitatively addressed.
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Control and Optimization,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Software
Reference29 articles.
1. Addis B, Locatelli M, Schoen F (2005) Local optima smoothing for global optimization. Opt Methods Softw 20(4–5):417–437. https://doi.org/10.1080/10556780500140029
2. Al-Garni A, Kassem AH (2005) Optimizing aerospace plane ascent trajectory with thermal constraints using genetic algorithms. In: A Collection of Technical Papers–13th AIAA/CIRA International Space Planes and Hypersonic Systems and Technologies Conference, vol 2, pp 849–853
3. Avanzini G, Biamonti D, Minisci E (2003) Minimum-Fuel/Minimum-Time Maneuvers of Formation Flying Satellites. In: Astrodynamics Specialist Conference, Washington, DC
4. Becerra VM (2012) Practical Direct Collocation Methods for Computational Optimal Control. Modeling and Optimization in Space Engineering, vol 73. Springer, New York, NY, pp 33–60
5. Betts JT (2010) Practical methods for optimal control and estimation using nonlinear programming, 2nd edn. SIAM, New Delhi
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献