A MODIFIED GENETIC ALGORITHM FOR THE DESIGN OF AUTONOMOUS HELICOPTER CONTROL SYSTEM

The use of genetic algorithms for solving aerospace control system design and optimization problems is investigated. A modified genetic algorithm based on floating point representation of the chromosome and appropriate genetic operators is developed and used to design controller gains for an autonomous airvehicle. The controller design problem is formulated along a classical pattern with requirements expressed both in time and frequency domain. Performance of the controlled system is compared with results obtained using a classical design procedure and with results obtained with a standard genetic algorithm using binary representation. Improvements of the algorithm performance are obtained using elitist selection strategy and selective weights in the evaluation function. Genetic algorithms show the potential of promising techniques for solving complex aerospace control system design problems.