3D Reference Trajectory Optimization Using Particle Swarm Optimization

2017 ◽  
Author(s):  
Alejandro Murrieta-Mendoza ◽  
Hugo Ruiz ◽  
Sonya Kessaci ◽  
Ruxandra Mihaela Botez
Keyword(s):  
Particle Swarm Optimization ◽  
Trajectory Optimization ◽  
Particle Swarm ◽  
Reference Trajectory ◽  
Swarm Optimization

Coevolutionary Algorithm Applied to Skip Reentry Trajectory Optimization Design

2013 ◽  
Vol 427-429 ◽  
pp. 1424-1431
Author(s):  
Feng Bo Wang ◽  
Chang Hong Dong
Keyword(s):  
Particle Swarm Optimization ◽  
Trajectory Optimization ◽  
Optimization Design ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Great Accuracy ◽  
Swarm Optimization ◽  
Coevolutionary Algorithm ◽  
Global Optima ◽  
Reentry Trajectory Optimization

This paper proposed a coevolutionary algorithm combining improved particle swarm optimization algorithm with differential evolution method and its application was provided. Adaptive position escapable mechanism is introduced in the particle swarm optimization to improve the diversity of population and guarantee to achieve the global optima. The differential algorithm is employed in a cooperative manner to maintain the characteristic of fast convergence speed in the later convergence phase. The coevolutionary algorithm is then applied to skip trajectory optimization design for crew exploration vehicle with low-lift-to-drag and several comparative cases are conducted, Results show that coevolutionary algorithm is quite effective in finding the global optimal solution with great accuracy.

Gliding Trajectory Optimization Method Based on Particle Swarm Optimization and Direct Shooting Method

2014 ◽  
Vol 615 ◽  
pp. 270-275
Author(s):  
Wen Jing Zhang ◽  
Fen Fen Xiong
Keyword(s):  
Particle Swarm Optimization ◽  
Trajectory Optimization ◽  
Direct Method ◽  
Angle Of Attack ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Direct Shooting ◽  
Direct And Indirect Methods

Glide trajectory optimization of vehicle can greatly improve the performance of missile. As is well-known, methods of trajectory optimization can be divided into direct and indirect methods. Generally, the direct method is convenient and can obtain the optimal solution with higher probability. Based on the direct method, a missile trajectory is optimized by discretizing the control quantity (angle of attack) and transforming the original optimal control problem to a nonlinear programing problem (NLP) in the present paper. The particle swarm optimization algorithm that is easy to implement and has higher convergence rate is utilized to solve the transformed NLP to generate the optimal angle of attack rule. Simulation results show that with the optimal rule, gliding distance of missile is clearly improved compared to the initial one.

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