Abstract:

The spacecraft rendezvous problem of transferring between two coplanar elliptical orbits with free time is studied, which looks for multi-impulsive transfer at the expense of fuel optimization under lots of constraints. Different number of pulses will change the number of variables to solve optimization problems. Through the introduction of hidden genes in the genetic algorithm, the individuals in the gene groups have a variable-length feature. The optimal solution to the number of pulses and impulse vectors is obtained at the same time. In order to further improve the optimal solution, an initial coast is introduced to be as an optimal variable, which results in the just pulse moment of de-orbit for chaser. Firstly， a genetic algorithm is applied to find initial guess values, and then the sequential quadratic programming (SQP) algorithm is used to iteratively improve the above non-optimal solution and converge to a global optimal transferring. Finally, on the base of the primer vector theory and control optimal criterion, it indicates that the hidden genes hybrid genetic algorithm can serve -as an effective optimization method to solve effectively a class of complex problems, in addition the multipulse rendezvous guidance law design which includes variable number of variables optimized also can successfully be done.