The purpose of the present study was to design a flight control system with no pre-determined mathematical model, but instead using a genetic algorithm to maintain the optimal altitude. The study is d..
The purpose of the present study was to design a flight control system with no pre-determined mathematical model, but instead using a genetic algorithm to maintain the optimal altitude. The study is done through a quantitative empirical research method. In the process of conducting the research, we found that programming a genetic algorithm was cumbersome for novice users to implement. Due to this, we created and released an open source Python package called EasyGA. An initial population of 10 chromosomes and 5 generations were used during the trial. The throttle value of the device had an associated gene value of 1 second. When the trial of five generations was completed, the total increase percentage was 171 percent. Preliminary results showed that optimizing a one DOF device, in real-time, is possible without using a pre-determined mathematical model.
