Abstract
In this paper, two types of optimization strategies are applied to solve the Space Manoeuvre Vehicle (SMV) trajectory optimization problem. The SMV dynamic model is constructed and discretized applying direct multiple shooting method. To solve the resulting Nonlinear Programming (NLP) problem, gradient-based and derivative free optimization techniques are used to calculate the optimal time history with respect to the states and controls. Simulation results indicate that the proposed strategies are effective and can provide feasible solutions for solving the constrained SMV trajectory design problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Betts JT (1998) Survey of numerical methods for trajectory optimization. J Guidance Control Dyn 21(2):193–207. https://dx.doi.org/10.2514/2.4231
Chai R, Savvaris A, Tsourdos A (2016) Fuzzy physical programming for space manoeuvre vehicles trajectory optimization based on hp-adaptive pseudospectral method. Acta Astronautica 123:62–70. https://dx.doi.org/10.1016/j.actaastro.2016.02.020
Dingni, Z., Yi, L.: RLV reentry trajectory optimization through hybridization of an improved GA and a SQP algorithm. In: Guidance navigation, and control and co-located conferences. American Institute of Aeronautics and Astronautics (2011). https://dx.doi.org/10.2514/6.2011-6658
Gan, C., Zi-ming, W., Min, X., Si-lu, C.: Genetic algorithm optimization of RLV reentry trajectory. In: International space planes and hypersonic systems and technologies conferences. American Institute of Aeronautics and Astronautics (2005). https://dx.doi.org/10.2514/6.2005-3269
Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm. J Glob Optim 39(3):459–471. https://dx.doi.org/10.1007/s10898-007-9149-x
Kenan, Z., Wanchun, C.: Reentry vehicle constrained trajectory optimization. In: International space planes and hypersonic systems and technologies conferences. American Institute of Aeronautics and Astronautics (2011). https://dx.doi.org/10.2514/6.2011-2231
Peter, G., Klaus, W.: Trajectory optimization using a combination of direct multiple shooting and collocation. In: Guidance, navigation, and control and co-located conferences. American Institute of Aeronautics and Astronautics (2001). https://dx.doi.org/10.2514/6.2001-404710.2514/6.2001-4047
Rahimi A, Dev Kumar K, Alighanbari H (2012) Particle swarm optimization applied to spacecraft reentry trajectory. J Guidance Control Dyn 36(1):307–310. https://dx.doi.org/10.2514/1.56387
Rajesh, A.: Reentry trajectory optimization: evolutionary approach. In: Multidisciplinary analysis optimization conferences. American Institute of Aeronautics and Astronautics (2002). https://dx.doi.org/10.2514/6.2002-5466
Reddien GW (1979) Collocation at gauss points as a discretization in optimal control. SIAM J Control Optim 17(2):298–306. https://dx.doi.org/10.1137/0317023
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Chai, R., Savvaris, A., Tsourdos, A. (2018). Analysis of Optimization Strategies for Solving Space Manoeuvre Vehicle Trajectory Optimization Problem. In: Dołęga, B., Głębocki, R., Kordos, D., Żugaj, M. (eds) Advances in Aerospace Guidance, Navigation and Control. Springer, Cham. https://doi.org/10.1007/978-3-319-65283-2_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-65283-2_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65282-5
Online ISBN: 978-3-319-65283-2
eBook Packages: EngineeringEngineering (R0)