Authors:
Eugene Semenkin
and
Maria Semenkina
Affiliation:
Siberian State Aerospace University, Russian Federation
Keyword(s):
Spacecraft Control System, Control Contours Models, Markov Chains, Effective Variant Choice, Optimization, Self-configuring Genetic Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Decision Support Systems
;
Engineering Applications
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
Abstract:
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.