Robust and Optimal Trajectory design of a Launch vehicle Upper stage using Genetic algorithm and Particle Swarm Optimization

Document Type : Research Paper

Authors

1 Faculty of Aerospace, Malek Ashtar University of Technology, Tehran

2 Faculty of Aerospace, Malek Ashtar University of Technology, Iran.

Abstract

In engineering problems, one of the most important parameters affecting the results is the existence of uncertainties. In many engineering problems, it is not possible to accurately predict the parameters and factors affecting it, and in the best case, they can only be estimated. In this article, the UpperStage of a special launcher is selected as a study case and the robust optimization method is used to solve the design problem of its trajectory, until the final trajectory is Robust to the presence of uncertainties in the actual values of engine thrust and mass in the ascent phase. Therefore, in order to achieve this goal, the optimization problem with the criterion function of fuel consumption minimization by using the equations of motion of three degrees of freedom has been considered as the governing equations of the problem. In the following, the average parameters and standard deviation of uncertainties are added and the robust optimizer model is developed. In order to solve the optimization problem, in this article two methods of genetic algorithm and particle swarm algorithm are used to solve the optimization problem. Also, for investigating and analyzing the effect of uncertainties in the calculation process, the Monte Carlo method has been used. Finally, the simulation results show that the Robust optimal trajectory has improved the altitude error by nearly 77%, the orbital speed error by 68%, and the path angle error by nearly 90% in the presence of uncertainties. The simulation results show the truth of this claim.

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