论文信息 - Spacecrafts' Control Systems Effective Variants Choice with Self-configuring Genetic Algorithm

Spacecrafts' Control Systems Effective Variants Choice with Self-configuring Genetic Algorithm

The work of the spacecraft control system is modeled with Markov chains. Small and large models for the technological and command-programming control contours are developed. The way of the calculation of the control contour effectiveness indicators is described. Special self-configuring genetic algorithm that requires no settings determination and parameter tuning is proposed for choosing effective variants of spacecraft control system. The high performance of the suggested algorithm is demonstrated through experiments with test problems and then is validated by the solving hard optimization problems.

Eugene Semenkin | Maria Semenkina

[1] Randy L. Haupt,et al. Practical Genetic Algorithms , 1998 .

[2] Gilbert Syswerda,et al. Uniform Crossover in Genetic Algorithms , 1989, ICGA.

[3] Hans-Georg Beyer,et al. Self-Adaptation in Evolutionary Algorithms , 2007, Parameter Setting in Evolutionary Algorithms.

[4] W. Spears,et al. On the Virtues of Parameterized Uniform Crossover , 1995 .

[5] Jonatan Gómez,et al. Self Adaptation of Operator Rates in Evolutionary Algorithms , 2004, GECCO.

[6] Zbigniew Michalewicz,et al. Parameter Control in Evolutionary Algorithms , 2007, Parameter Setting in Evolutionary Algorithms.

[7] Peter J. Angeline,et al. Adaptive and Self-adaptive Evolutionary Computations , 1995 .

[8] A. E. Eiben,et al. Introduction to Evolutionary Computing , 2003, Natural Computing Series.