Controller Design for Autonomous Helicopter Model Using a Genetic Algorithm

Genetic algorithms (GAs) are parameter search techniques that rely on analogies to natural biological processes. The purpose of this paper is to investigate the use of GAs for airvehicle control system design. The case of an autonomous helicopter model is considered. The design of the gains for the longitudinal channel is formulated and solved as a complex, constrained, nonlinear, multiple objective problem. Design requirements are formulated both in time and frequency domain following an often used pattern. A classical genetic algorithm is implemented using binary representation, roulette wheel selection technique, standard mutation and crossover operators. Effects of selective weights in the evaluation function and elitist selection strategy are analyzed. Performance of the controlled system is compared to results obtained using a classical design procedure. GAs show the potential of promising techniques for solving complex aerospace control system design problems.