Control system optimization using genetic algorithms

Abstract

The use of genetic algorithms as a technique for solving aerospace-related control system optimization problems is explored in this paper. Genetic algorithms are parameter search procedures based on the mechanics of natural genetics. They combine a Darwinian survival-of-the-fittest strategy with a random yet structured information exchange among a population of artificial chromosomes. The genetic algorithm technique is used to design a lateral autopilot and a windshear controller. The results show that a variety of aerospace control system optimization problems can be addressed using genetic algorithms with no special problem-dependent modifications. Suggestions for other uses related to aerospace control system optimization are presented.