Interactive Optimization Approach for Optimal Impulsive Rendezvous Using Primer Vector and Evolutionary Algorithms
- Paper number
IAC-08.C1.2.11
- Author
Dr. Ya-Zhong Luo, National University of Defense Technology, China
- Coauthor
Mr. Jin Zhang, National University of Defence Technology, China
- Coauthor
Dr. Guo-jin Tang, National University of Defense Technology, China
- Coauthor
Dr. Hai-yang Li, National University of Defense Technology, China
- Year
2008
- Abstract
The fuel-optimal rendezvous problem has been extensively studied, and a lot of algorithms have been proposed. The existing algorithms can guarantee to obtain a global solution for the linearized impulsive rendezvous, but not so efficient and effective in solving the nonlinear rendezvous problems. In this paper, a new interactive optimization approach combining the advantages of the classical theories and the evolutionary algorithms for impulsive fuel-optimal rendezvous is proposed which both optimizes the number of impulses and the impulse vectors. In this interactive approach, the primer vector theory is employed to decide whether to add an impulse by figuring the primer vector. And the evolutionary algorithms are employed to optimize the best rendezvous trajectory with the fixed number of impulses. Different evolutionary algorithms including genetic algorithm, simulated annealing, hybrid genetic algorithm, and parallel simulated annealing are compared and the best one in finally employed in this interactive approach. The procedure of the interactive optimization approach is described detailed. The interactive approach is evaluated by three test cases: a homing rendezvous problem, a same-circle rendezvous problem and a non-coplanar rendezvous problem. The results show that the interactive approach is effective and efficient in optimizing the nonlinear rendezvous. It can guarantee the solutions which satisfy the Lawden’s necessary optimality conditions.
- Abstract document
- Manuscript document
IAC-08.C1.2.11.pdf (🔒 authorized access only).
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